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eeeba562221d0bc6c7708c93ac7230eeba0c080a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: elozano/tweet_offensive_eval
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-tweet_eval-offensive-f58805-30720144959
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:04:36+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["tweet_eval"], "eval_info": {"task": "multi_class_classification", "model": "elozano/tweet_offensive_eval", "metrics": ["bertscore"], "dataset_name": "tweet_eval", "dataset_config": "offensive", "dataset_split": "train", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T13:05:44+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Multi-class Text Classification
* Model: elozano/tweet_offensive_eval
* Dataset: tweet_eval
* Config: offensive
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @fabeelaalirawther@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: elozano/tweet_offensive_eval\n* Dataset: tweet_eval\n* Config: offensive\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @fabeelaalirawther@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: elozano/tweet_offensive_eval\n* Dataset: tweet_eval\n* Config: offensive\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @fabeelaalirawther@URL for evaluating this model."
] |
[
13,
92,
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[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: elozano/tweet_offensive_eval\n* Dataset: tweet_eval\n* Config: offensive\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @fabeelaalirawther@URL for evaluating this model."
] |
9540916d94354b7fac5709d7a6110ea71eb46cd7
|
# Dataset Card for "test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tessiw/test
|
[
"region:us"
] |
2023-10-04T13:05:23+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train2", "path": "data/train2-*"}]}], "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "system_prompt", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "response", "dtype": "string"}], "splits": [{"name": "train2", "num_bytes": 1754, "num_examples": 3}], "download_size": 6433, "dataset_size": 1754}}
|
2023-10-04T13:07:26+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "test"
More Information needed
|
[
"# Dataset Card for \"test\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"test\"\n\nMore Information needed"
] |
[
6,
11
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[
"passage: TAGS\n#region-us \n# Dataset Card for \"test\"\n\nMore Information needed"
] |
90f129393a2ec4a1272ddbeb956a0fda75b8fda6
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-67ab09-31609144969
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:06:10+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "0ys/mt5-small-finetuned-amazon-en-es", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:11:55+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @malar for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
13,
98,
14
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[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @malar for evaluating this model."
] |
dccfd17db093803b2ca3f8574c2c5c35638012e7
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-ilpost
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-67ab09-31609144970
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:06:19+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ARTeLab/it5-summarization-ilpost", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:16:23+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-ilpost
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @malar for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-ilpost\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-ilpost\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
13,
91,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-ilpost\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @malar for evaluating this model."
] |
a0b924f4f5fe15ae138110c7952c78221fe2b067
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-37f310-31613144971
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:06:29+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "0ys/mt5-small-finetuned-amazon-en-es", "metrics": ["rouge"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:12:03+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @malar for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
13,
98,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @malar for evaluating this model."
] |
d45727f86ea0d354707639bb01b57d3088852c58
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-ilpost
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-37f310-31613144972
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:06:38+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ARTeLab/it5-summarization-ilpost", "metrics": ["rouge"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:16:47+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-ilpost
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @malar for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-ilpost\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-ilpost\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
13,
91,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-ilpost\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @malar for evaluating this model."
] |
522deb5cf2a42cf3048831528099afea4d0e64b8
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@malar](https://huggingface.co/malar) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-37f310-31613144973
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:06:47+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ARTeLab/it5-summarization-fanpage", "metrics": ["rouge"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:17:01+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @malar for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @malar for evaluating this model."
] |
[
13,
91,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @malar for evaluating this model."
] |
fb6fd382716055fe26563436f4d947c0622f5f00
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sr5434](https://huggingface.co/sr5434) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-e1b364-31627144974
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:06:56+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ARTeLab/it5-summarization-fanpage", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:17:00+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @sr5434 for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sr5434 for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sr5434 for evaluating this model."
] |
[
13,
91,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @sr5434 for evaluating this model."
] |
f0a18a183cdf69c040fae346d7794ae5306b30f5
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg
* Dataset: multi_nli
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@2552](https://huggingface.co/2552) for evaluating this model.
|
autoevaluate/autoeval-eval-multi_nli-default-725a45-31703144975
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:07:05+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["multi_nli"], "eval_info": {"task": "natural_language_inference", "model": "HiTZ/A2T_RoBERTa_SMFA_ACE-arg", "metrics": [], "dataset_name": "multi_nli", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"text1": "premise", "text2": "hypothesis", "target": "label"}}}
|
2023-10-04T14:14:29+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Natural Language Inference
* Model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg
* Dataset: multi_nli
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @2552 for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Natural Language Inference\n* Model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg\n* Dataset: multi_nli\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @2552 for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Natural Language Inference\n* Model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg\n* Dataset: multi_nli\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @2552 for evaluating this model."
] |
[
13,
96,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Natural Language Inference\n* Model: HiTZ/A2T_RoBERTa_SMFA_ACE-arg\n* Dataset: multi_nli\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @2552 for evaluating this model."
] |
6a50bfa4530ad81c496532c4aa740438007d88ec
|
# Dataset Card for "contracts_v1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
paul-w-qs/contracts_v1
|
[
"region:us"
] |
2023-10-04T13:08:38+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "ground_truth", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 296160099.824, "num_examples": 3052}, {"name": "validation", "num_bytes": 71579695.0, "num_examples": 764}, {"name": "test", "num_bytes": 91333831.0, "num_examples": 955}], "download_size": 457070753, "dataset_size": 459073625.824}}
|
2023-10-04T13:24:27+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "contracts_v1"
More Information needed
|
[
"# Dataset Card for \"contracts_v1\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"contracts_v1\"\n\nMore Information needed"
] |
[
6,
15
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"contracts_v1\"\n\nMore Information needed"
] |
95d2149cb03ce402f53b7bde72f899d73afe7929
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: sschet/biobert_chemical_ner
* Dataset: drAbreu/bc4chemd_ner
* Config: bc4chemd
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sschet](https://huggingface.co/sschet) for evaluating this model.
|
autoevaluate/autoeval-eval-drAbreu__bc4chemd_ner-bc4chemd-aa2b75-31927145000
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:11:07+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["drAbreu/bc4chemd_ner"], "eval_info": {"task": "entity_extraction", "model": "sschet/biobert_chemical_ner", "metrics": [], "dataset_name": "drAbreu/bc4chemd_ner", "dataset_config": "bc4chemd", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}}
|
2023-10-04T13:16:15+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: sschet/biobert_chemical_ner
* Dataset: drAbreu/bc4chemd_ner
* Config: bc4chemd
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @sschet for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: sschet/biobert_chemical_ner\n* Dataset: drAbreu/bc4chemd_ner\n* Config: bc4chemd\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sschet for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: sschet/biobert_chemical_ner\n* Dataset: drAbreu/bc4chemd_ner\n* Config: bc4chemd\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sschet for evaluating this model."
] |
[
13,
100,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: sschet/biobert_chemical_ner\n* Dataset: drAbreu/bc4chemd_ner\n* Config: bc4chemd\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @sschet for evaluating this model."
] |
167d522bd1d5e96afbc989d458a0a55e464ab280
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: PoseyATX/Moist-Pony
* Dataset: billsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@poseyatx](https://huggingface.co/poseyatx) for evaluating this model.
|
autoevaluate/autoeval-eval-billsum-default-bec98f-32334145011
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:12:55+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["billsum"], "eval_info": {"task": "summarization", "model": "PoseyATX/Moist-Pony", "metrics": [], "dataset_name": "billsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "summary"}}}
|
2023-10-04T13:28:44+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: PoseyATX/Moist-Pony
* Dataset: billsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @poseyatx for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: PoseyATX/Moist-Pony\n* Dataset: billsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @poseyatx for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: PoseyATX/Moist-Pony\n* Dataset: billsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @poseyatx for evaluating this model."
] |
[
13,
85,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: PoseyATX/Moist-Pony\n* Dataset: billsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @poseyatx for evaluating this model."
] |
474fe07bfc828566697c169b2d662f6a67317bf1
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: Alred/t5-small-finetuned-summarization-cnn
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@dfantasy](https://huggingface.co/dfantasy) for evaluating this model.
|
autoevaluate/autoeval-eval-xsum-default-403a15-33262145014
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:13:23+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xsum"], "eval_info": {"task": "summarization", "model": "Alred/t5-small-finetuned-summarization-cnn", "metrics": [], "dataset_name": "xsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:15:56+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: Alred/t5-small-finetuned-summarization-cnn
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @dfantasy for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Alred/t5-small-finetuned-summarization-cnn\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @dfantasy for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Alred/t5-small-finetuned-summarization-cnn\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @dfantasy for evaluating this model."
] |
[
13,
93,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Alred/t5-small-finetuned-summarization-cnn\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @dfantasy for evaluating this model."
] |
1b2143060356a4ae3aa8290951b557ddff825adf
|
# Dataset Card for Evaluation run of bongchoi/test-llama2-70b
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/bongchoi/test-llama2-70b
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [bongchoi/test-llama2-70b](https://huggingface.co/bongchoi/test-llama2-70b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_bongchoi__test-llama2-70b",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-04T14:13:10.692338](https://huggingface.co/datasets/open-llm-leaderboard/details_bongchoi__test-llama2-70b/blob/main/results_2023-10-04T14-13-10.692338.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.6967225637378714,
"acc_stderr": 0.030867069907791145,
"acc_norm": 0.7008615431872544,
"acc_norm_stderr": 0.030836865817034945,
"mc1": 0.3108935128518972,
"mc1_stderr": 0.016203316673559696,
"mc2": 0.44923493721887353,
"mc2_stderr": 0.01390226410719232
},
"harness|arc:challenge|25": {
"acc": 0.6262798634812287,
"acc_stderr": 0.014137708601759091,
"acc_norm": 0.6732081911262798,
"acc_norm_stderr": 0.013706665975587333
},
"harness|hellaswag|10": {
"acc": 0.6760605457080263,
"acc_stderr": 0.00467020812857923,
"acc_norm": 0.8733320055765784,
"acc_norm_stderr": 0.0033192094001351187
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.33,
"acc_stderr": 0.04725815626252605,
"acc_norm": 0.33,
"acc_norm_stderr": 0.04725815626252605
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6296296296296297,
"acc_stderr": 0.04171654161354544,
"acc_norm": 0.6296296296296297,
"acc_norm_stderr": 0.04171654161354544
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.8092105263157895,
"acc_stderr": 0.031975658210325,
"acc_norm": 0.8092105263157895,
"acc_norm_stderr": 0.031975658210325
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.72,
"acc_stderr": 0.04512608598542127,
"acc_norm": 0.72,
"acc_norm_stderr": 0.04512608598542127
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7169811320754716,
"acc_stderr": 0.027724236492700918,
"acc_norm": 0.7169811320754716,
"acc_norm_stderr": 0.027724236492700918
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.8472222222222222,
"acc_stderr": 0.030085743248565666,
"acc_norm": 0.8472222222222222,
"acc_norm_stderr": 0.030085743248565666
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.51,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.51,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.6,
"acc_stderr": 0.049236596391733084,
"acc_norm": 0.6,
"acc_norm_stderr": 0.049236596391733084
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.37,
"acc_stderr": 0.048523658709391,
"acc_norm": 0.37,
"acc_norm_stderr": 0.048523658709391
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6416184971098265,
"acc_stderr": 0.03656343653353159,
"acc_norm": 0.6416184971098265,
"acc_norm_stderr": 0.03656343653353159
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.37254901960784315,
"acc_stderr": 0.04810840148082635,
"acc_norm": 0.37254901960784315,
"acc_norm_stderr": 0.04810840148082635
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.77,
"acc_stderr": 0.04229525846816506,
"acc_norm": 0.77,
"acc_norm_stderr": 0.04229525846816506
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.6638297872340425,
"acc_stderr": 0.030881618520676942,
"acc_norm": 0.6638297872340425,
"acc_norm_stderr": 0.030881618520676942
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4473684210526316,
"acc_stderr": 0.04677473004491199,
"acc_norm": 0.4473684210526316,
"acc_norm_stderr": 0.04677473004491199
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.6551724137931034,
"acc_stderr": 0.03960933549451207,
"acc_norm": 0.6551724137931034,
"acc_norm_stderr": 0.03960933549451207
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.43386243386243384,
"acc_stderr": 0.025525034382474894,
"acc_norm": 0.43386243386243384,
"acc_norm_stderr": 0.025525034382474894
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.47619047619047616,
"acc_stderr": 0.04467062628403273,
"acc_norm": 0.47619047619047616,
"acc_norm_stderr": 0.04467062628403273
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.46,
"acc_stderr": 0.05009082659620332,
"acc_norm": 0.46,
"acc_norm_stderr": 0.05009082659620332
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.8193548387096774,
"acc_stderr": 0.02188617856717253,
"acc_norm": 0.8193548387096774,
"acc_norm_stderr": 0.02188617856717253
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5123152709359606,
"acc_stderr": 0.035169204442208966,
"acc_norm": 0.5123152709359606,
"acc_norm_stderr": 0.035169204442208966
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.79,
"acc_stderr": 0.040936018074033256,
"acc_norm": 0.79,
"acc_norm_stderr": 0.040936018074033256
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.8303030303030303,
"acc_stderr": 0.029311188674983134,
"acc_norm": 0.8303030303030303,
"acc_norm_stderr": 0.029311188674983134
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.8787878787878788,
"acc_stderr": 0.023253157951942084,
"acc_norm": 0.8787878787878788,
"acc_norm_stderr": 0.023253157951942084
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.9430051813471503,
"acc_stderr": 0.016731085293607555,
"acc_norm": 0.9430051813471503,
"acc_norm_stderr": 0.016731085293607555
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.7410256410256411,
"acc_stderr": 0.02221110681006167,
"acc_norm": 0.7410256410256411,
"acc_norm_stderr": 0.02221110681006167
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.35555555555555557,
"acc_stderr": 0.029185714949857403,
"acc_norm": 0.35555555555555557,
"acc_norm_stderr": 0.029185714949857403
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.7647058823529411,
"acc_stderr": 0.02755361446786381,
"acc_norm": 0.7647058823529411,
"acc_norm_stderr": 0.02755361446786381
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.4304635761589404,
"acc_stderr": 0.04042809961395634,
"acc_norm": 0.4304635761589404,
"acc_norm_stderr": 0.04042809961395634
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8733944954128441,
"acc_stderr": 0.014257128686165169,
"acc_norm": 0.8733944954128441,
"acc_norm_stderr": 0.014257128686165169
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.6342592592592593,
"acc_stderr": 0.032847388576472056,
"acc_norm": 0.6342592592592593,
"acc_norm_stderr": 0.032847388576472056
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8970588235294118,
"acc_stderr": 0.02132833757080437,
"acc_norm": 0.8970588235294118,
"acc_norm_stderr": 0.02132833757080437
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.8776371308016878,
"acc_stderr": 0.021331741829746786,
"acc_norm": 0.8776371308016878,
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"harness|hendrycksTest-human_aging|5": {
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"harness|hendrycksTest-international_law|5": {
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"harness|hendrycksTest-jurisprudence|5": {
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"harness|hendrycksTest-nutrition|5": {
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"harness|hendrycksTest-philosophy|5": {
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"harness|hendrycksTest-prehistory|5": {
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"acc_norm": 0.8364197530864198,
"acc_norm_stderr": 0.020581466138257114
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"harness|hendrycksTest-professional_accounting|5": {
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"harness|hendrycksTest-professional_law|5": {
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"harness|hendrycksTest-public_relations|5": {
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"harness|hendrycksTest-security_studies|5": {
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"harness|hendrycksTest-us_foreign_policy|5": {
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"harness|hendrycksTest-virology|5": {
"acc": 0.5301204819277109,
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"acc_norm": 0.5301204819277109,
"acc_norm_stderr": 0.03885425420866767
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"harness|hendrycksTest-world_religions|5": {
"acc": 0.8538011695906432,
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"harness|truthfulqa:mc|0": {
"mc1": 0.3108935128518972,
"mc1_stderr": 0.016203316673559696,
"mc2": 0.44923493721887353,
"mc2_stderr": 0.01390226410719232
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed]
|
open-llm-leaderboard/details_bongchoi__test-llama2-70b
|
[
"region:us"
] |
2023-10-04T13:13:29+00:00
|
{"pretty_name": "Evaluation run of bongchoi/test-llama2-70b", "dataset_summary": "Dataset automatically created during the evaluation run of model [bongchoi/test-llama2-70b](https://huggingface.co/bongchoi/test-llama2-70b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\nTo load the details from a run, you can for instance do the following:\n```python\nfrom datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_bongchoi__test-llama2-70b\",\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2023-10-04T14:13:10.692338](https://huggingface.co/datasets/open-llm-leaderboard/details_bongchoi__test-llama2-70b/blob/main/results_2023-10-04T14-13-10.692338.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6967225637378714,\n \"acc_stderr\": 0.030867069907791145,\n \"acc_norm\": 0.7008615431872544,\n \"acc_norm_stderr\": 0.030836865817034945,\n \"mc1\": 0.3108935128518972,\n \"mc1_stderr\": 0.016203316673559696,\n \"mc2\": 0.44923493721887353,\n \"mc2_stderr\": 0.01390226410719232\n },\n \"harness|arc:challenge|25\": {\n \"acc\": 0.6262798634812287,\n \"acc_stderr\": 0.014137708601759091,\n \"acc_norm\": 0.6732081911262798,\n \"acc_norm_stderr\": 0.013706665975587333\n },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6760605457080263,\n \"acc_stderr\": 0.00467020812857923,\n \"acc_norm\": 0.8733320055765784,\n \"acc_norm_stderr\": 0.0033192094001351187\n },\n \"harness|hendrycksTest-abstract_algebra|5\": {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6296296296296297,\n \"acc_stderr\": 0.04171654161354544,\n \"acc_norm\": 0.6296296296296297,\n \"acc_norm_stderr\": 0.04171654161354544\n },\n \"harness|hendrycksTest-astronomy|5\": {\n \"acc\": 0.8092105263157895,\n \"acc_stderr\": 0.031975658210325,\n \"acc_norm\": 0.8092105263157895,\n \"acc_norm_stderr\": 0.031975658210325\n },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542127\n },\n \"harness|hendrycksTest-clinical_knowledge|5\": {\n \"acc\": 0.7169811320754716,\n \"acc_stderr\": 0.027724236492700918,\n \"acc_norm\": 0.7169811320754716,\n \"acc_norm_stderr\": 0.027724236492700918\n },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8472222222222222,\n \"acc_stderr\": 0.030085743248565666,\n \"acc_norm\": 0.8472222222222222,\n \"acc_norm_stderr\": 0.030085743248565666\n },\n \"harness|hendrycksTest-college_chemistry|5\": {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.37,\n \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6416184971098265,\n \"acc_stderr\": 0.03656343653353159,\n \"acc_norm\": 0.6416184971098265,\n \"acc_norm_stderr\": 0.03656343653353159\n },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082635,\n \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082635\n },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\": 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.77,\n \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\": 0.6638297872340425,\n \"acc_stderr\": 0.030881618520676942,\n \"acc_norm\": 0.6638297872340425,\n \"acc_norm_stderr\": 0.030881618520676942\n },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4473684210526316,\n \"acc_stderr\": 0.04677473004491199,\n \"acc_norm\": 0.4473684210526316,\n \"acc_norm_stderr\": 0.04677473004491199\n },\n \"harness|hendrycksTest-electrical_engineering|5\": {\n \"acc\": 0.6551724137931034,\n \"acc_stderr\": 0.03960933549451207,\n \"acc_norm\": 0.6551724137931034,\n \"acc_norm_stderr\": 0.03960933549451207\n },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.43386243386243384,\n \"acc_stderr\": 0.025525034382474894,\n \"acc_norm\": 0.43386243386243384,\n \"acc_norm_stderr\": 0.025525034382474894\n },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.47619047619047616,\n \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.47619047619047616,\n \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8193548387096774,\n \"acc_stderr\": 0.02188617856717253,\n \"acc_norm\": 0.8193548387096774,\n \"acc_norm_stderr\": 0.02188617856717253\n },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\": 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n \"acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-high_school_european_history|5\": {\n \"acc\": 0.8303030303030303,\n \"acc_stderr\": 0.029311188674983134,\n \"acc_norm\": 0.8303030303030303,\n \"acc_norm_stderr\": 0.029311188674983134\n },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\": 0.8787878787878788,\n \"acc_stderr\": 0.023253157951942084,\n \"acc_norm\": 0.8787878787878788,\n \"acc_norm_stderr\": 0.023253157951942084\n },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \"acc\": 0.9430051813471503,\n \"acc_stderr\": 0.016731085293607555,\n \"acc_norm\": 0.9430051813471503,\n \"acc_norm_stderr\": 0.016731085293607555\n },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \"acc\": 0.7410256410256411,\n \"acc_stderr\": 0.02221110681006167,\n \"acc_norm\": 0.7410256410256411,\n \"acc_norm_stderr\": 0.02221110681006167\n },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"acc\": 0.35555555555555557,\n \"acc_stderr\": 0.029185714949857403,\n \"acc_norm\": 0.35555555555555557,\n \"acc_norm_stderr\": 0.029185714949857403\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \"acc\": 0.7647058823529411,\n \"acc_stderr\": 0.02755361446786381,\n \"acc_norm\": 0.7647058823529411,\n \"acc_norm_stderr\": 0.02755361446786381\n },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\": 0.4304635761589404,\n \"acc_stderr\": 0.04042809961395634,\n \"acc_norm\": 0.4304635761589404,\n \"acc_norm_stderr\": 0.04042809961395634\n },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.8733944954128441,\n \"acc_stderr\": 0.014257128686165169,\n \"acc_norm\": 0.8733944954128441,\n \"acc_norm_stderr\": 0.014257128686165169\n },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\": 0.6342592592592593,\n \"acc_stderr\": 0.032847388576472056,\n \"acc_norm\": 0.6342592592592593,\n \"acc_norm_stderr\": 0.032847388576472056\n },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.8970588235294118,\n \"acc_stderr\": 0.02132833757080437,\n \"acc_norm\": 0.8970588235294118,\n \"acc_norm_stderr\": 0.02132833757080437\n },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\": 0.8776371308016878,\n \"acc_stderr\": 0.021331741829746786,\n \"acc_norm\": 0.8776371308016878,\n \"acc_norm_stderr\": 0.021331741829746786\n },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.8026905829596412,\n \"acc_stderr\": 0.02670985334496796,\n \"acc_norm\": 0.8026905829596412,\n \"acc_norm_stderr\": 0.02670985334496796\n },\n \"harness|hendrycksTest-human_sexuality|5\": {\n \"acc\": 0.8778625954198473,\n \"acc_stderr\": 0.028718776889342344,\n \"acc_norm\": 0.8778625954198473,\n \"acc_norm_stderr\": 0.028718776889342344\n },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\": 0.8760330578512396,\n \"acc_stderr\": 0.03008309871603521,\n \"acc_norm\": 0.8760330578512396,\n \"acc_norm_stderr\": 0.03008309871603521\n },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8333333333333334,\n \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness|hendrycksTest-logical_fallacies|5\": {\n \"acc\": 0.803680981595092,\n \"acc_stderr\": 0.031207970394709218,\n \"acc_norm\": 0.803680981595092,\n \"acc_norm_stderr\": 0.031207970394709218\n },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5357142857142857,\n \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.5357142857142857,\n \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\": {\n \"acc\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.905982905982906,\n \"acc_stderr\": 0.01911989279892498,\n \"acc_norm\": 0.905982905982906,\n \"acc_norm_stderr\": 0.01911989279892498\n },\n \"harness|hendrycksTest-medical_genetics|5\": {\n \"acc\": 0.74,\n \"acc_stderr\": 0.04408440022768077,\n \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.04408440022768077\n },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8620689655172413,\n \"acc_stderr\": 0.012331009307795656,\n \"acc_norm\": 0.8620689655172413,\n \"acc_norm_stderr\": 0.012331009307795656\n },\n \"harness|hendrycksTest-moral_disputes|5\": {\n \"acc\": 0.7774566473988439,\n \"acc_stderr\": 0.02239421566194282,\n \"acc_norm\": 0.7774566473988439,\n \"acc_norm_stderr\": 0.02239421566194282\n },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4547486033519553,\n \"acc_stderr\": 0.016653875777524012,\n \"acc_norm\": 0.4547486033519553,\n \"acc_norm_stderr\": 0.016653875777524012\n },\n \"harness|hendrycksTest-nutrition|5\": {\n \"acc\": 0.7810457516339869,\n \"acc_stderr\": 0.02367908986180772,\n \"acc_norm\": 0.7810457516339869,\n \"acc_norm_stderr\": 0.02367908986180772\n },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7877813504823151,\n \"acc_stderr\": 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2023-10-04T13:14:30+00:00
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TAGS
#region-us
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# Dataset Card for Evaluation run of bongchoi/test-llama2-70b
## Dataset Description
- Homepage:
- Repository: URL
- Paper:
- Leaderboard: URL
- Point of Contact: clementine@URL
### Dataset Summary
Dataset automatically created during the evaluation run of model bongchoi/test-llama2-70b on the Open LLM Leaderboard.
The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the Open LLM Leaderboard).
To load the details from a run, you can for instance do the following:
## Latest results
These are the latest results from run 2023-10-04T14:13:10.692338(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### Annotation process
#### Who are the annotators?
### Personal and Sensitive Information
## Considerations for Using the Data
### Social Impact of Dataset
### Discussion of Biases
### Other Known Limitations
## Additional Information
### Dataset Curators
### Licensing Information
### Contributions
|
[
"# Dataset Card for Evaluation run of bongchoi/test-llama2-70b",
"## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL",
"### Dataset Summary\n\nDataset automatically created during the evaluation run of model bongchoi/test-llama2-70b on the Open LLM Leaderboard.\n\nThe dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:",
"## Latest results\n\nThese are the latest results from run 2023-10-04T14:13:10.692338(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### Annotation process",
"#### Who are the annotators?",
"### Personal and Sensitive Information",
"## Considerations for Using the Data",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations",
"## Additional Information",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of bongchoi/test-llama2-70b",
"## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL",
"### Dataset Summary\n\nDataset automatically created during the evaluation run of model bongchoi/test-llama2-70b on the Open LLM Leaderboard.\n\nThe dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:",
"## Latest results\n\nThese are the latest results from run 2023-10-04T14:13:10.692338(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):",
"### Supported Tasks and Leaderboards",
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"### Data Instances",
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"### Personal and Sensitive Information",
"## Considerations for Using the Data",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations",
"## Additional Information",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] |
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[
"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of bongchoi/test-llama2-70b## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL### Dataset Summary\n\nDataset automatically created during the evaluation run of model bongchoi/test-llama2-70b on the Open LLM Leaderboard.\n\nThe dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:## Latest results\n\nThese are the latest results from run 2023-10-04T14:13:10.692338(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information## Considerations for Using the Data### Social Impact of Dataset### Discussion of Biases### Other Known Limitations## Additional Information### Dataset Curators### Licensing Information### Contributions"
] |
88d4af0f31be510ad938b9b4b445eafccf19df7e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-small
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@thefirebanks](https://huggingface.co/thefirebanks) for evaluating this model.
|
autoevaluate/autoeval-eval-xsum-default-cf6255-33263145015
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:13:34+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xsum"], "eval_info": {"task": "summarization", "model": "t5-small", "metrics": [], "dataset_name": "xsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:16:03+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: t5-small
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @thefirebanks for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-small\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @thefirebanks for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-small\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @thefirebanks for evaluating this model."
] |
[
13,
79,
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[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-small\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @thefirebanks for evaluating this model."
] |
e3f0e1bd2a8ff686aee5f9ee692e11e68fde418e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-small
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@dfantasy](https://huggingface.co/dfantasy) for evaluating this model.
|
autoevaluate/autoeval-eval-xsum-default-01da82-33500145018
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:14:03+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xsum"], "eval_info": {"task": "summarization", "model": "t5-small", "metrics": [], "dataset_name": "xsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:16:30+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: t5-small
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @dfantasy for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-small\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @dfantasy for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-small\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @dfantasy for evaluating this model."
] |
[
13,
79,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-small\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @dfantasy for evaluating this model."
] |
06fd5954004a34259731c2b79a05f98d58b1a10d
|
# Chat Fine-tuning Dataset - Llama 2 Style
This dataset allows for fine-tuning chat models using [INST] AND [/INST] to wrap user messages.
Preparation:
1. The dataset is cloned from [TimDettmers](https://huggingface.co/datasets/timdettmers/openassistant-guanaco), which itself is a subset of the Open Assistant dataset, which you can find [here](https://huggingface.co/datasets/OpenAssistant/oasst1/tree/main). This subset of the data only contains the highest-rated paths in the conversation tree, with a total of 9,846 samples.
1. The dataset was then filtered to:
- replace instances of '### Human:' with '[INST]'
- replace instances of '### Assistant:' with '</s><s> [/INST]' (to encourage the model to emit </s> when finished a response)
- if a row of data ends with an assistant response, then [INST] was additionally added to the end of that row of data.
Details of the root dataset follow, copied from that repo:
# OpenAssistant Conversations Dataset (OASST1)
## Dataset Description
- **Homepage:** https://www.open-assistant.io/
- **Repository:** https://github.com/LAION-AI/Open-Assistant
- **Paper:** https://arxiv.org/abs/2304.07327
### Dataset Summary
In an effort to democratize research on large-scale alignment, we release OpenAssistant
Conversations (OASST1), a human-generated, human-annotated assistant-style conversation
corpus consisting of 161,443 messages in 35 different languages, annotated with 461,292
quality ratings, resulting in over 10,000 fully annotated conversation trees. The corpus
is a product of a worldwide crowd-sourcing effort involving over 13,500 volunteers.
Please refer to our [paper](https://arxiv.org/abs/2304.07327) for further details.
### Dataset Structure
This dataset contains message trees. Each message tree has an initial prompt message as the root node,
which can have multiple child messages as replies, and these child messages can have multiple replies.
All messages have a role property: this can either be "assistant" or "prompter". The roles in
conversation threads from prompt to leaf node strictly alternate between "prompter" and "assistant".
This version of the dataset contains data collected on the [open-assistant.io](https://open-assistant.io/) website until April 12 2023.
### JSON Example: Message
For readability, the following JSON examples are shown formatted with indentation on multiple lines.
Objects are stored without indentation (on single lines) in the actual jsonl files.
```json
{
"message_id": "218440fd-5317-4355-91dc-d001416df62b",
"parent_id": "13592dfb-a6f9-4748-a92c-32b34e239bb4",
"user_id": "8e95461f-5e94-4d8b-a2fb-d4717ce973e4",
"text": "It was the winter of 2035, and artificial intelligence (..)",
"role": "assistant",
"lang": "en",
"review_count": 3,
"review_result": true,
"deleted": false,
"rank": 0,
"synthetic": true,
"model_name": "oasst-sft-0_3000,max_new_tokens=400 (..)",
"labels": {
"spam": { "value": 0.0, "count": 3 },
"lang_mismatch": { "value": 0.0, "count": 3 },
"pii": { "value": 0.0, "count": 3 },
"not_appropriate": { "value": 0.0, "count": 3 },
"hate_speech": { "value": 0.0, "count": 3 },
"sexual_content": { "value": 0.0, "count": 3 },
"quality": { "value": 0.416, "count": 3 },
"toxicity": { "value": 0.16, "count": 3 },
"humor": { "value": 0.0, "count": 3 },
"creativity": { "value": 0.33, "count": 3 },
"violence": { "value": 0.16, "count": 3 }
}
}
```
### JSON Example: Conversation Tree
For readability, only a subset of the message properties is shown here.
```json
{
"message_tree_id": "14fbb664-a620-45ce-bee4-7c519b16a793",
"tree_state": "ready_for_export",
"prompt": {
"message_id": "14fbb664-a620-45ce-bee4-7c519b16a793",
"text": "Why can't we divide by 0? (..)",
"role": "prompter",
"lang": "en",
"replies": [
{
"message_id": "894d30b6-56b4-4605-a504-89dd15d4d1c8",
"text": "The reason we cannot divide by zero is because (..)",
"role": "assistant",
"lang": "en",
"replies": [
// ...
]
},
{
"message_id": "84d0913b-0fd9-4508-8ef5-205626a7039d",
"text": "The reason that the result of a division by zero is (..)",
"role": "assistant",
"lang": "en",
"replies": [
{
"message_id": "3352725e-f424-4e3b-a627-b6db831bdbaa",
"text": "Math is confusing. Like those weird Irrational (..)",
"role": "prompter",
"lang": "en",
"replies": [
{
"message_id": "f46207ca-3149-46e9-a466-9163d4ce499c",
"text": "Irrational numbers are simply numbers (..)",
"role": "assistant",
"lang": "en",
"replies": []
},
// ...
]
}
]
}
]
}
}
```
Please refer to [oasst-data](https://github.com/LAION-AI/Open-Assistant/tree/main/oasst-data) for
details about the data structure and Python code to read and write jsonl files containing oasst data objects.
If you would like to explore the dataset yourself you can find a
[`getting-started`](https://github.com/LAION-AI/Open-Assistant/blob/main/notebooks/openassistant-oasst1/getting-started.ipynb)
notebook in the `notebooks/openassistant-oasst1` folder of the [LAION-AI/Open-Assistant](https://github.com/LAION-AI/Open-Assistant)
github repository.
## Main Dataset Files
Conversation data is provided either as nested messages in trees (extension `.trees.jsonl.gz`)
or as a flat list (table) of messages (extension `.messages.jsonl.gz`).
### Ready For Export Trees
```
2023-04-12_oasst_ready.trees.jsonl.gz 10,364 trees with 88,838 total messages
2023-04-12_oasst_ready.messages.jsonl.gz 88,838 messages
```
Trees in `ready_for_export` state without spam and deleted messages including message labels.
The oasst_ready-trees file usually is sufficient for supervised fine-tuning (SFT) & reward model (RM) training.
### All Trees
```
2023-04-12_oasst_all.trees.jsonl.gz 66,497 trees with 161,443 total messages
2023-04-12_oasst_all.messages.jsonl.gz 161,443 messages
```
All trees, including those in states `prompt_lottery_waiting` (trees that consist of only one message, namely the initial prompt),
`aborted_low_grade` (trees that stopped growing because the messages had low quality), and `halted_by_moderator`.
### Supplemental Exports: Spam & Prompts
```
2023-04-12_oasst_spam.messages.jsonl.gz
```
These are messages which were deleted or have a negative review result (`"review_result": false`).
Besides low quality, a frequent reason for message deletion is a wrong language tag.
```
2023-04-12_oasst_prompts.messages.jsonl.gz
```
These are all the kept initial prompt messages with positive review result (no spam) of trees in `ready_for_export` or `prompt_lottery_waiting` state.
### Using the Huggingface Datasets
While HF datasets is ideal for tabular datasets, it is not a natural fit for nested data structures like the OpenAssistant conversation trees.
Nevertheless, we make all messages which can also be found in the file `2023-04-12_oasst_ready.trees.jsonl.gz` available in parquet as train/validation splits.
These are directly loadable by [Huggingface Datasets](https://pypi.org/project/datasets/).
To load the oasst1 train & validation splits use:
```python
from datasets import load_dataset
ds = load_dataset("OpenAssistant/oasst1")
train = ds['train'] # len(train)=84437 (95%)
val = ds['validation'] # len(val)=4401 (5%)
```
The messages appear in depth-first order of the message trees.
Full conversation trees can be reconstructed from the flat messages table by using the `parent_id`
and `message_id` properties to identify the parent-child relationship of messages. The `message_tree_id`
and `tree_state` properties (only present in flat messages files) can be used to find all messages of a message tree or to select trees by their state.
### Languages
OpenAssistant Conversations incorporates 35 different languages with a distribution of messages as follows:
**Languages with over 1000 messages**
- English: 71956
- Spanish: 43061
- Russian: 9089
- German: 5279
- Chinese: 4962
- French: 4251
- Thai: 3042
- Portuguese (Brazil): 2969
- Catalan: 2260
- Korean: 1553
- Ukrainian: 1352
- Italian: 1320
- Japanese: 1018
<details>
<summary><b>Languages with under 1000 messages</b></summary>
<ul>
<li>Vietnamese: 952</li>
<li>Basque: 947</li>
<li>Polish: 886</li>
<li>Hungarian: 811</li>
<li>Arabic: 666</li>
<li>Dutch: 628</li>
<li>Swedish: 512</li>
<li>Turkish: 454</li>
<li>Finnish: 386</li>
<li>Czech: 372</li>
<li>Danish: 358</li>
<li>Galician: 339</li>
<li>Hebrew: 255</li>
<li>Romanian: 200</li>
<li>Norwegian Bokmål: 133</li>
<li>Indonesian: 115</li>
<li>Bulgarian: 95</li>
<li>Bengali: 82</li>
<li>Persian: 72</li>
<li>Greek: 66</li>
<li>Esperanto: 59</li>
<li>Slovak: 19</li>
</ul>
</details>
## Contact
- Discord [Open Assistant Discord Server](https://ykilcher.com/open-assistant-discord)
- GitHub: [LAION-AI/Open-Assistant](https://github.com/LAION-AI/Open-Assistant)
- E-Mail: [[email protected]](mailto:[email protected])
|
Trelis/openassistant-llama-style
|
[
"size_categories:1K<n<10k",
"language:en",
"language:es",
"language:ru",
"language:de",
"language:pl",
"language:th",
"language:vi",
"language:sv",
"language:bn",
"language:da",
"language:he",
"language:it",
"language:fa",
"language:sk",
"language:id",
"language:nb",
"language:el",
"language:nl",
"language:hu",
"language:eu",
"language:zh",
"language:eo",
"language:ja",
"language:ca",
"language:cs",
"language:bg",
"language:fi",
"language:pt",
"language:tr",
"language:ro",
"language:ar",
"language:uk",
"language:gl",
"language:fr",
"language:ko",
"license:apache-2.0",
"human-feedback",
"llama-2",
"arxiv:2304.07327",
"region:us"
] |
2023-10-04T13:14:13+00:00
|
{"language": ["en", "es", "ru", "de", "pl", "th", "vi", "sv", "bn", "da", "he", "it", "fa", "sk", "id", "nb", "el", "nl", "hu", "eu", "zh", "eo", "ja", "ca", "cs", "bg", "fi", "pt", "tr", "ro", "ar", "uk", "gl", "fr", "ko"], "license": "apache-2.0", "size_categories": ["1K<n<10k"], "pretty_name": "Filtered OpenAssistant Conversations", "tags": ["human-feedback", "llama-2"]}
|
2023-10-31T11:29:33+00:00
|
[
"2304.07327"
] |
[
"en",
"es",
"ru",
"de",
"pl",
"th",
"vi",
"sv",
"bn",
"da",
"he",
"it",
"fa",
"sk",
"id",
"nb",
"el",
"nl",
"hu",
"eu",
"zh",
"eo",
"ja",
"ca",
"cs",
"bg",
"fi",
"pt",
"tr",
"ro",
"ar",
"uk",
"gl",
"fr",
"ko"
] |
TAGS
#size_categories-1K<n<10k #language-English #language-Spanish #language-Russian #language-German #language-Polish #language-Thai #language-Vietnamese #language-Swedish #language-Bengali #language-Danish #language-Hebrew #language-Italian #language-Persian #language-Slovak #language-Indonesian #language-Norwegian Bokmål #language-Modern Greek (1453-) #language-Dutch #language-Hungarian #language-Basque #language-Chinese #language-Esperanto #language-Japanese #language-Catalan #language-Czech #language-Bulgarian #language-Finnish #language-Portuguese #language-Turkish #language-Romanian #language-Arabic #language-Ukrainian #language-Galician #language-French #language-Korean #license-apache-2.0 #human-feedback #llama-2 #arxiv-2304.07327 #region-us
|
# Chat Fine-tuning Dataset - Llama 2 Style
This dataset allows for fine-tuning chat models using [INST] AND [/INST] to wrap user messages.
Preparation:
1. The dataset is cloned from TimDettmers, which itself is a subset of the Open Assistant dataset, which you can find here. This subset of the data only contains the highest-rated paths in the conversation tree, with a total of 9,846 samples.
1. The dataset was then filtered to:
- replace instances of '### Human:' with '[INST]'
- replace instances of '### Assistant:' with '</s><s> [/INST]' (to encourage the model to emit </s> when finished a response)
- if a row of data ends with an assistant response, then [INST] was additionally added to the end of that row of data.
Details of the root dataset follow, copied from that repo:
# OpenAssistant Conversations Dataset (OASST1)
## Dataset Description
- Homepage: URL
- Repository: URL
- Paper: URL
### Dataset Summary
In an effort to democratize research on large-scale alignment, we release OpenAssistant
Conversations (OASST1), a human-generated, human-annotated assistant-style conversation
corpus consisting of 161,443 messages in 35 different languages, annotated with 461,292
quality ratings, resulting in over 10,000 fully annotated conversation trees. The corpus
is a product of a worldwide crowd-sourcing effort involving over 13,500 volunteers.
Please refer to our paper for further details.
### Dataset Structure
This dataset contains message trees. Each message tree has an initial prompt message as the root node,
which can have multiple child messages as replies, and these child messages can have multiple replies.
All messages have a role property: this can either be "assistant" or "prompter". The roles in
conversation threads from prompt to leaf node strictly alternate between "prompter" and "assistant".
This version of the dataset contains data collected on the URL website until April 12 2023.
### JSON Example: Message
For readability, the following JSON examples are shown formatted with indentation on multiple lines.
Objects are stored without indentation (on single lines) in the actual jsonl files.
### JSON Example: Conversation Tree
For readability, only a subset of the message properties is shown here.
Please refer to oasst-data for
details about the data structure and Python code to read and write jsonl files containing oasst data objects.
If you would like to explore the dataset yourself you can find a
'getting-started'
notebook in the 'notebooks/openassistant-oasst1' folder of the LAION-AI/Open-Assistant
github repository.
## Main Dataset Files
Conversation data is provided either as nested messages in trees (extension '.URL')
or as a flat list (table) of messages (extension '.URL').
### Ready For Export Trees
Trees in 'ready_for_export' state without spam and deleted messages including message labels.
The oasst_ready-trees file usually is sufficient for supervised fine-tuning (SFT) & reward model (RM) training.
### All Trees
All trees, including those in states 'prompt_lottery_waiting' (trees that consist of only one message, namely the initial prompt),
'aborted_low_grade' (trees that stopped growing because the messages had low quality), and 'halted_by_moderator'.
### Supplemental Exports: Spam & Prompts
These are messages which were deleted or have a negative review result ('"review_result": false').
Besides low quality, a frequent reason for message deletion is a wrong language tag.
These are all the kept initial prompt messages with positive review result (no spam) of trees in 'ready_for_export' or 'prompt_lottery_waiting' state.
### Using the Huggingface Datasets
While HF datasets is ideal for tabular datasets, it is not a natural fit for nested data structures like the OpenAssistant conversation trees.
Nevertheless, we make all messages which can also be found in the file '2023-04-12_oasst_ready.URL' available in parquet as train/validation splits.
These are directly loadable by Huggingface Datasets.
To load the oasst1 train & validation splits use:
The messages appear in depth-first order of the message trees.
Full conversation trees can be reconstructed from the flat messages table by using the 'parent_id'
and 'message_id' properties to identify the parent-child relationship of messages. The 'message_tree_id'
and 'tree_state' properties (only present in flat messages files) can be used to find all messages of a message tree or to select trees by their state.
### Languages
OpenAssistant Conversations incorporates 35 different languages with a distribution of messages as follows:
Languages with over 1000 messages
- English: 71956
- Spanish: 43061
- Russian: 9089
- German: 5279
- Chinese: 4962
- French: 4251
- Thai: 3042
- Portuguese (Brazil): 2969
- Catalan: 2260
- Korean: 1553
- Ukrainian: 1352
- Italian: 1320
- Japanese: 1018
<details>
<summary><b>Languages with under 1000 messages</b></summary>
<ul>
<li>Vietnamese: 952</li>
<li>Basque: 947</li>
<li>Polish: 886</li>
<li>Hungarian: 811</li>
<li>Arabic: 666</li>
<li>Dutch: 628</li>
<li>Swedish: 512</li>
<li>Turkish: 454</li>
<li>Finnish: 386</li>
<li>Czech: 372</li>
<li>Danish: 358</li>
<li>Galician: 339</li>
<li>Hebrew: 255</li>
<li>Romanian: 200</li>
<li>Norwegian Bokmål: 133</li>
<li>Indonesian: 115</li>
<li>Bulgarian: 95</li>
<li>Bengali: 82</li>
<li>Persian: 72</li>
<li>Greek: 66</li>
<li>Esperanto: 59</li>
<li>Slovak: 19</li>
</ul>
</details>
## Contact
- Discord Open Assistant Discord Server
- GitHub: LAION-AI/Open-Assistant
- E-Mail: open-assistant@URL
|
[
"# Chat Fine-tuning Dataset - Llama 2 Style\nThis dataset allows for fine-tuning chat models using [INST] AND [/INST] to wrap user messages.\n\nPreparation:\n\n1. The dataset is cloned from TimDettmers, which itself is a subset of the Open Assistant dataset, which you can find here. This subset of the data only contains the highest-rated paths in the conversation tree, with a total of 9,846 samples.\n1. The dataset was then filtered to:\n - replace instances of '### Human:' with '[INST]'\n - replace instances of '### Assistant:' with '</s><s> [/INST]' (to encourage the model to emit </s> when finished a response)\n - if a row of data ends with an assistant response, then [INST] was additionally added to the end of that row of data.\n\nDetails of the root dataset follow, copied from that repo:",
"# OpenAssistant Conversations Dataset (OASST1)",
"## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL",
"### Dataset Summary\n\nIn an effort to democratize research on large-scale alignment, we release OpenAssistant \nConversations (OASST1), a human-generated, human-annotated assistant-style conversation \ncorpus consisting of 161,443 messages in 35 different languages, annotated with 461,292 \nquality ratings, resulting in over 10,000 fully annotated conversation trees. The corpus \nis a product of a worldwide crowd-sourcing effort involving over 13,500 volunteers.\n\nPlease refer to our paper for further details.",
"### Dataset Structure\n\nThis dataset contains message trees. Each message tree has an initial prompt message as the root node, \nwhich can have multiple child messages as replies, and these child messages can have multiple replies. \n\nAll messages have a role property: this can either be \"assistant\" or \"prompter\". The roles in \nconversation threads from prompt to leaf node strictly alternate between \"prompter\" and \"assistant\".\n\nThis version of the dataset contains data collected on the URL website until April 12 2023.",
"### JSON Example: Message\n\nFor readability, the following JSON examples are shown formatted with indentation on multiple lines.\nObjects are stored without indentation (on single lines) in the actual jsonl files.",
"### JSON Example: Conversation Tree\n\nFor readability, only a subset of the message properties is shown here.\n\n\n\nPlease refer to oasst-data for\ndetails about the data structure and Python code to read and write jsonl files containing oasst data objects.\n\nIf you would like to explore the dataset yourself you can find a \n'getting-started' \nnotebook in the 'notebooks/openassistant-oasst1' folder of the LAION-AI/Open-Assistant\ngithub repository.",
"## Main Dataset Files\n\nConversation data is provided either as nested messages in trees (extension '.URL') \nor as a flat list (table) of messages (extension '.URL').",
"### Ready For Export Trees\n\n\nTrees in 'ready_for_export' state without spam and deleted messages including message labels.\nThe oasst_ready-trees file usually is sufficient for supervised fine-tuning (SFT) & reward model (RM) training.",
"### All Trees\n\nAll trees, including those in states 'prompt_lottery_waiting' (trees that consist of only one message, namely the initial prompt),\n'aborted_low_grade' (trees that stopped growing because the messages had low quality), and 'halted_by_moderator'.",
"### Supplemental Exports: Spam & Prompts\n\nThese are messages which were deleted or have a negative review result ('\"review_result\": false').\nBesides low quality, a frequent reason for message deletion is a wrong language tag.\n\n\nThese are all the kept initial prompt messages with positive review result (no spam) of trees in 'ready_for_export' or 'prompt_lottery_waiting' state.",
"### Using the Huggingface Datasets\n\nWhile HF datasets is ideal for tabular datasets, it is not a natural fit for nested data structures like the OpenAssistant conversation trees.\nNevertheless, we make all messages which can also be found in the file '2023-04-12_oasst_ready.URL' available in parquet as train/validation splits. \nThese are directly loadable by Huggingface Datasets.\n\nTo load the oasst1 train & validation splits use:\n\n\n\nThe messages appear in depth-first order of the message trees.\n\nFull conversation trees can be reconstructed from the flat messages table by using the 'parent_id' \nand 'message_id' properties to identify the parent-child relationship of messages. The 'message_tree_id' \nand 'tree_state' properties (only present in flat messages files) can be used to find all messages of a message tree or to select trees by their state.",
"### Languages\n\nOpenAssistant Conversations incorporates 35 different languages with a distribution of messages as follows:\n\nLanguages with over 1000 messages\n- English: 71956\n- Spanish: 43061\n- Russian: 9089\n- German: 5279\n- Chinese: 4962\n- French: 4251\n- Thai: 3042\n- Portuguese (Brazil): 2969\n- Catalan: 2260\n- Korean: 1553\n- Ukrainian: 1352\n- Italian: 1320\n- Japanese: 1018\n\n<details>\n <summary><b>Languages with under 1000 messages</b></summary>\n <ul>\n <li>Vietnamese: 952</li>\n <li>Basque: 947</li>\n <li>Polish: 886</li>\n <li>Hungarian: 811</li>\n <li>Arabic: 666</li>\n <li>Dutch: 628</li>\n <li>Swedish: 512</li>\n <li>Turkish: 454</li>\n <li>Finnish: 386</li>\n <li>Czech: 372</li>\n <li>Danish: 358</li>\n <li>Galician: 339</li>\n <li>Hebrew: 255</li>\n <li>Romanian: 200</li>\n <li>Norwegian Bokmål: 133</li>\n <li>Indonesian: 115</li>\n <li>Bulgarian: 95</li>\n <li>Bengali: 82</li>\n <li>Persian: 72</li>\n <li>Greek: 66</li>\n <li>Esperanto: 59</li>\n <li>Slovak: 19</li>\n </ul>\n</details>",
"## Contact\n\n- Discord Open Assistant Discord Server\n- GitHub: LAION-AI/Open-Assistant\n- E-Mail: open-assistant@URL"
] |
[
"TAGS\n#size_categories-1K<n<10k #language-English #language-Spanish #language-Russian #language-German #language-Polish #language-Thai #language-Vietnamese #language-Swedish #language-Bengali #language-Danish #language-Hebrew #language-Italian #language-Persian #language-Slovak #language-Indonesian #language-Norwegian Bokmål #language-Modern Greek (1453-) #language-Dutch #language-Hungarian #language-Basque #language-Chinese #language-Esperanto #language-Japanese #language-Catalan #language-Czech #language-Bulgarian #language-Finnish #language-Portuguese #language-Turkish #language-Romanian #language-Arabic #language-Ukrainian #language-Galician #language-French #language-Korean #license-apache-2.0 #human-feedback #llama-2 #arxiv-2304.07327 #region-us \n",
"# Chat Fine-tuning Dataset - Llama 2 Style\nThis dataset allows for fine-tuning chat models using [INST] AND [/INST] to wrap user messages.\n\nPreparation:\n\n1. The dataset is cloned from TimDettmers, which itself is a subset of the Open Assistant dataset, which you can find here. This subset of the data only contains the highest-rated paths in the conversation tree, with a total of 9,846 samples.\n1. The dataset was then filtered to:\n - replace instances of '### Human:' with '[INST]'\n - replace instances of '### Assistant:' with '</s><s> [/INST]' (to encourage the model to emit </s> when finished a response)\n - if a row of data ends with an assistant response, then [INST] was additionally added to the end of that row of data.\n\nDetails of the root dataset follow, copied from that repo:",
"# OpenAssistant Conversations Dataset (OASST1)",
"## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL",
"### Dataset Summary\n\nIn an effort to democratize research on large-scale alignment, we release OpenAssistant \nConversations (OASST1), a human-generated, human-annotated assistant-style conversation \ncorpus consisting of 161,443 messages in 35 different languages, annotated with 461,292 \nquality ratings, resulting in over 10,000 fully annotated conversation trees. The corpus \nis a product of a worldwide crowd-sourcing effort involving over 13,500 volunteers.\n\nPlease refer to our paper for further details.",
"### Dataset Structure\n\nThis dataset contains message trees. Each message tree has an initial prompt message as the root node, \nwhich can have multiple child messages as replies, and these child messages can have multiple replies. \n\nAll messages have a role property: this can either be \"assistant\" or \"prompter\". The roles in \nconversation threads from prompt to leaf node strictly alternate between \"prompter\" and \"assistant\".\n\nThis version of the dataset contains data collected on the URL website until April 12 2023.",
"### JSON Example: Message\n\nFor readability, the following JSON examples are shown formatted with indentation on multiple lines.\nObjects are stored without indentation (on single lines) in the actual jsonl files.",
"### JSON Example: Conversation Tree\n\nFor readability, only a subset of the message properties is shown here.\n\n\n\nPlease refer to oasst-data for\ndetails about the data structure and Python code to read and write jsonl files containing oasst data objects.\n\nIf you would like to explore the dataset yourself you can find a \n'getting-started' \nnotebook in the 'notebooks/openassistant-oasst1' folder of the LAION-AI/Open-Assistant\ngithub repository.",
"## Main Dataset Files\n\nConversation data is provided either as nested messages in trees (extension '.URL') \nor as a flat list (table) of messages (extension '.URL').",
"### Ready For Export Trees\n\n\nTrees in 'ready_for_export' state without spam and deleted messages including message labels.\nThe oasst_ready-trees file usually is sufficient for supervised fine-tuning (SFT) & reward model (RM) training.",
"### All Trees\n\nAll trees, including those in states 'prompt_lottery_waiting' (trees that consist of only one message, namely the initial prompt),\n'aborted_low_grade' (trees that stopped growing because the messages had low quality), and 'halted_by_moderator'.",
"### Supplemental Exports: Spam & Prompts\n\nThese are messages which were deleted or have a negative review result ('\"review_result\": false').\nBesides low quality, a frequent reason for message deletion is a wrong language tag.\n\n\nThese are all the kept initial prompt messages with positive review result (no spam) of trees in 'ready_for_export' or 'prompt_lottery_waiting' state.",
"### Using the Huggingface Datasets\n\nWhile HF datasets is ideal for tabular datasets, it is not a natural fit for nested data structures like the OpenAssistant conversation trees.\nNevertheless, we make all messages which can also be found in the file '2023-04-12_oasst_ready.URL' available in parquet as train/validation splits. \nThese are directly loadable by Huggingface Datasets.\n\nTo load the oasst1 train & validation splits use:\n\n\n\nThe messages appear in depth-first order of the message trees.\n\nFull conversation trees can be reconstructed from the flat messages table by using the 'parent_id' \nand 'message_id' properties to identify the parent-child relationship of messages. The 'message_tree_id' \nand 'tree_state' properties (only present in flat messages files) can be used to find all messages of a message tree or to select trees by their state.",
"### Languages\n\nOpenAssistant Conversations incorporates 35 different languages with a distribution of messages as follows:\n\nLanguages with over 1000 messages\n- English: 71956\n- Spanish: 43061\n- Russian: 9089\n- German: 5279\n- Chinese: 4962\n- French: 4251\n- Thai: 3042\n- Portuguese (Brazil): 2969\n- Catalan: 2260\n- Korean: 1553\n- Ukrainian: 1352\n- Italian: 1320\n- Japanese: 1018\n\n<details>\n <summary><b>Languages with under 1000 messages</b></summary>\n <ul>\n <li>Vietnamese: 952</li>\n <li>Basque: 947</li>\n <li>Polish: 886</li>\n <li>Hungarian: 811</li>\n <li>Arabic: 666</li>\n <li>Dutch: 628</li>\n <li>Swedish: 512</li>\n <li>Turkish: 454</li>\n <li>Finnish: 386</li>\n <li>Czech: 372</li>\n <li>Danish: 358</li>\n <li>Galician: 339</li>\n <li>Hebrew: 255</li>\n <li>Romanian: 200</li>\n <li>Norwegian Bokmål: 133</li>\n <li>Indonesian: 115</li>\n <li>Bulgarian: 95</li>\n <li>Bengali: 82</li>\n <li>Persian: 72</li>\n <li>Greek: 66</li>\n <li>Esperanto: 59</li>\n <li>Slovak: 19</li>\n </ul>\n</details>",
"## Contact\n\n- Discord Open Assistant Discord Server\n- GitHub: LAION-AI/Open-Assistant\n- E-Mail: open-assistant@URL"
] |
[
239,
213,
15,
18,
120,
120,
51,
117,
46,
66,
74,
99,
221,
381,
36
] |
[
"passage: TAGS\n#size_categories-1K<n<10k #language-English #language-Spanish #language-Russian #language-German #language-Polish #language-Thai #language-Vietnamese #language-Swedish #language-Bengali #language-Danish #language-Hebrew #language-Italian #language-Persian #language-Slovak #language-Indonesian #language-Norwegian Bokmål #language-Modern Greek (1453-) #language-Dutch #language-Hungarian #language-Basque #language-Chinese #language-Esperanto #language-Japanese #language-Catalan #language-Czech #language-Bulgarian #language-Finnish #language-Portuguese #language-Turkish #language-Romanian #language-Arabic #language-Ukrainian #language-Galician #language-French #language-Korean #license-apache-2.0 #human-feedback #llama-2 #arxiv-2304.07327 #region-us \n# Chat Fine-tuning Dataset - Llama 2 Style\nThis dataset allows for fine-tuning chat models using [INST] AND [/INST] to wrap user messages.\n\nPreparation:\n\n1. The dataset is cloned from TimDettmers, which itself is a subset of the Open Assistant dataset, which you can find here. This subset of the data only contains the highest-rated paths in the conversation tree, with a total of 9,846 samples.\n1. The dataset was then filtered to:\n - replace instances of '### Human:' with '[INST]'\n - replace instances of '### Assistant:' with '</s><s> [/INST]' (to encourage the model to emit </s> when finished a response)\n - if a row of data ends with an assistant response, then [INST] was additionally added to the end of that row of data.\n\nDetails of the root dataset follow, copied from that repo:# OpenAssistant Conversations Dataset (OASST1)## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL",
"passage: ### Dataset Summary\n\nIn an effort to democratize research on large-scale alignment, we release OpenAssistant \nConversations (OASST1), a human-generated, human-annotated assistant-style conversation \ncorpus consisting of 161,443 messages in 35 different languages, annotated with 461,292 \nquality ratings, resulting in over 10,000 fully annotated conversation trees. The corpus \nis a product of a worldwide crowd-sourcing effort involving over 13,500 volunteers.\n\nPlease refer to our paper for further details.### Dataset Structure\n\nThis dataset contains message trees. Each message tree has an initial prompt message as the root node, \nwhich can have multiple child messages as replies, and these child messages can have multiple replies. \n\nAll messages have a role property: this can either be \"assistant\" or \"prompter\". The roles in \nconversation threads from prompt to leaf node strictly alternate between \"prompter\" and \"assistant\".\n\nThis version of the dataset contains data collected on the URL website until April 12 2023.### JSON Example: Message\n\nFor readability, the following JSON examples are shown formatted with indentation on multiple lines.\nObjects are stored without indentation (on single lines) in the actual jsonl files.### JSON Example: Conversation Tree\n\nFor readability, only a subset of the message properties is shown here.\n\n\n\nPlease refer to oasst-data for\ndetails about the data structure and Python code to read and write jsonl files containing oasst data objects.\n\nIf you would like to explore the dataset yourself you can find a \n'getting-started' \nnotebook in the 'notebooks/openassistant-oasst1' folder of the LAION-AI/Open-Assistant\ngithub repository.## Main Dataset Files\n\nConversation data is provided either as nested messages in trees (extension '.URL') \nor as a flat list (table) of messages (extension '.URL').### Ready For Export Trees\n\n\nTrees in 'ready_for_export' state without spam and deleted messages including message labels.\nThe oasst_ready-trees file usually is sufficient for supervised fine-tuning (SFT) & reward model (RM) training.### All Trees\n\nAll trees, including those in states 'prompt_lottery_waiting' (trees that consist of only one message, namely the initial prompt),\n'aborted_low_grade' (trees that stopped growing because the messages had low quality), and 'halted_by_moderator'.",
"passage: ### Supplemental Exports: Spam & Prompts\n\nThese are messages which were deleted or have a negative review result ('\"review_result\": false').\nBesides low quality, a frequent reason for message deletion is a wrong language tag.\n\n\nThese are all the kept initial prompt messages with positive review result (no spam) of trees in 'ready_for_export' or 'prompt_lottery_waiting' state.### Using the Huggingface Datasets\n\nWhile HF datasets is ideal for tabular datasets, it is not a natural fit for nested data structures like the OpenAssistant conversation trees.\nNevertheless, we make all messages which can also be found in the file '2023-04-12_oasst_ready.URL' available in parquet as train/validation splits. \nThese are directly loadable by Huggingface Datasets.\n\nTo load the oasst1 train & validation splits use:\n\n\n\nThe messages appear in depth-first order of the message trees.\n\nFull conversation trees can be reconstructed from the flat messages table by using the 'parent_id' \nand 'message_id' properties to identify the parent-child relationship of messages. The 'message_tree_id' \nand 'tree_state' properties (only present in flat messages files) can be used to find all messages of a message tree or to select trees by their state."
] |
73e03ebc8969e6b7a8b0f5197d575e1c337b76fb
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: amazon_reviews_multi
* Config: en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Caxmann](https://huggingface.co/Caxmann) for evaluating this model.
|
autoevaluate/autoeval-eval-amazon_reviews_multi-en-4405a7-35409145025
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:15:12+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["amazon_reviews_multi"], "eval_info": {"task": "summarization", "model": "0ys/mt5-small-finetuned-amazon-en-es", "metrics": ["accuracy", "bertscore", "precision"], "dataset_name": "amazon_reviews_multi", "dataset_config": "en", "dataset_split": "test", "col_mapping": {"text": "review_body", "target": "review_title"}}}
|
2023-10-04T13:16:40+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: 0ys/mt5-small-finetuned-amazon-en-es
* Dataset: amazon_reviews_multi
* Config: en
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Caxmann for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: amazon_reviews_multi\n* Config: en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Caxmann for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: amazon_reviews_multi\n* Config: en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Caxmann for evaluating this model."
] |
[
13,
99,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0ys/mt5-small-finetuned-amazon-en-es\n* Dataset: amazon_reviews_multi\n* Config: en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Caxmann for evaluating this model."
] |
99b10b65128209164d11fb6fe40ed24d73042aff
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Mathking/bert-base-german-cased-gnad10
* Dataset: gnad10
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@BraveStone9](https://huggingface.co/BraveStone9) for evaluating this model.
|
autoevaluate/autoeval-eval-gnad10-default-1a81d6-36119145026
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:15:24+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["gnad10"], "eval_info": {"task": "multi_class_classification", "model": "Mathking/bert-base-german-cased-gnad10", "metrics": [], "dataset_name": "gnad10", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T13:16:33+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Mathking/bert-base-german-cased-gnad10
* Dataset: gnad10
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @BraveStone9 for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Mathking/bert-base-german-cased-gnad10\n* Dataset: gnad10\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @BraveStone9 for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Mathking/bert-base-german-cased-gnad10\n* Dataset: gnad10\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @BraveStone9 for evaluating this model."
] |
[
13,
95,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Mathking/bert-base-german-cased-gnad10\n* Dataset: gnad10\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @BraveStone9 for evaluating this model."
] |
b29545437b4358a40057b395b64dace56debf37e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@pszemraj](https://huggingface.co/pszemraj) for evaluating this model.
|
autoevaluate/autoeval-eval-xsum-default-79b8e9-36674145028
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:15:44+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xsum"], "eval_info": {"task": "summarization", "model": "stacked-summaries/flan-t5-large-stacked-xsum-1024", "metrics": [], "dataset_name": "xsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:48:13+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @pszemraj for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
13,
95,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
e55be8077d49bbd9c834d14952d3f0c4f164323a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: vvincentt/roberta_test
* Dataset: social_i_qa
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@kingmbc](https://huggingface.co/kingmbc) for evaluating this model.
|
autoevaluate/autoeval-eval-social_i_qa-default-cabb3b-37040145034
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:16:44+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["social_i_qa"], "eval_info": {"task": "extractive_question_answering", "model": "vvincentt/roberta_test", "metrics": [], "dataset_name": "social_i_qa", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"context": "context", "question": "question", "answers-text": "answerA", "answers-answer_start": "label"}}}
|
2023-10-04T13:23:06+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: vvincentt/roberta_test
* Dataset: social_i_qa
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @kingmbc for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: vvincentt/roberta_test\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: vvincentt/roberta_test\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
[
13,
87,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: vvincentt/roberta_test\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
01ae4eacf79f3f915dc73a1a5434ec4534ceeeed
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: 96harsh56/bert_test1
* Dataset: social_i_qa
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@kingmbc](https://huggingface.co/kingmbc) for evaluating this model.
|
autoevaluate/autoeval-eval-social_i_qa-default-cabb3b-37040145035
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:16:55+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["social_i_qa"], "eval_info": {"task": "extractive_question_answering", "model": "96harsh56/bert_test1", "metrics": [], "dataset_name": "social_i_qa", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"context": "context", "question": "question", "answers-text": "answerA", "answers-answer_start": "label"}}}
|
2023-10-04T13:23:10+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: 96harsh56/bert_test1
* Dataset: social_i_qa
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @kingmbc for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 96harsh56/bert_test1\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 96harsh56/bert_test1\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
[
13,
87,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 96harsh56/bert_test1\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
5f1de110a26cbd7b7b7502c4941cdc742d54da60
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: 21iridescent/distilroberta-base-finetuned-squad2-lwt
* Dataset: social_i_qa
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@kingmbc](https://huggingface.co/kingmbc) for evaluating this model.
|
autoevaluate/autoeval-eval-social_i_qa-default-cabb3b-37040145036
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:17:06+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["social_i_qa"], "eval_info": {"task": "extractive_question_answering", "model": "21iridescent/distilroberta-base-finetuned-squad2-lwt", "metrics": [], "dataset_name": "social_i_qa", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"context": "context", "question": "question", "answers-text": "answerA", "answers-answer_start": "label"}}}
|
2023-10-04T13:22:00+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: 21iridescent/distilroberta-base-finetuned-squad2-lwt
* Dataset: social_i_qa
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @kingmbc for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 21iridescent/distilroberta-base-finetuned-squad2-lwt\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 21iridescent/distilroberta-base-finetuned-squad2-lwt\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
[
13,
100,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 21iridescent/distilroberta-base-finetuned-squad2-lwt\n* Dataset: social_i_qa\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @kingmbc for evaluating this model."
] |
ac5658062a69118369813520ac1c889f64c11f26
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@qingxuwenli](https://huggingface.co/qingxuwenli) for evaluating this model.
|
autoevaluate/autoeval-eval-acronym_identification-default-7559c8-37651145037
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:17:15+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["acronym_identification"], "eval_info": {"task": "entity_extraction", "model": "lewtun/autotrain-acronym-identification-7324788", "metrics": ["angelina-wang/directional_bias_amplification"], "dataset_name": "acronym_identification", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"tokens": "tokens", "tags": "labels"}}}
|
2023-10-04T13:20:43+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @qingxuwenli for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
[
13,
96,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
04f8e0a2116d5d1d4fce7ba9ff928568f9731df4
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@qingxuwenli](https://huggingface.co/qingxuwenli) for evaluating this model.
|
autoevaluate/autoeval-eval-acronym_identification-default-b06490-37652145038
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:17:27+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["acronym_identification"], "eval_info": {"task": "entity_extraction", "model": "lewtun/autotrain-acronym-identification-7324788", "metrics": ["angelina-wang/directional_bias_amplification"], "dataset_name": "acronym_identification", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"tokens": "tokens", "tags": "labels"}}}
|
2023-10-04T13:20:51+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @qingxuwenli for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
[
13,
96,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
d478be448db12f1823c2de6c7aa300fc5136558f
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@qingxuwenli](https://huggingface.co/qingxuwenli) for evaluating this model.
|
autoevaluate/autoeval-eval-acronym_identification-default-ef327c-37654145039
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:17:36+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["acronym_identification"], "eval_info": {"task": "entity_extraction", "model": "lewtun/autotrain-acronym-identification-7324788", "metrics": ["angelina-wang/directional_bias_amplification"], "dataset_name": "acronym_identification", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"tokens": "tokens", "tags": "labels"}}}
|
2023-10-04T13:21:00+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @qingxuwenli for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
[
13,
96,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @qingxuwenli for evaluating this model."
] |
c36667b29b90295731ca17d47c111f7abe92e2a8
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: Akbar-Ali/autotrain-News_Summariser_Eng-1224546522
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@https://huggingface.co/Sini](https://huggingface.co/https://huggingface.co/Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-6c534f-38130145043
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:18:15+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "Akbar-Ali/autotrain-News_Summariser_Eng-1224546522", "metrics": ["rouge", "accuracy", "bleu"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T16:05:18+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: Akbar-Ali/autotrain-News_Summariser_Eng-1224546522
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Akbar-Ali/autotrain-News_Summariser_Eng-1224546522\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Akbar-Ali/autotrain-News_Summariser_Eng-1224546522\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
13,
100,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Akbar-Ali/autotrain-News_Summariser_Eng-1224546522\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @URL for evaluating this model."
] |
f4ed330ec30fe12a06f0d52f1344305a5a769c87
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: yuvraj/summarizer-cnndm
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@https://huggingface.co/Sini](https://huggingface.co/https://huggingface.co/Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-6c534f-38130145044
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:18:24+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "yuvraj/summarizer-cnndm", "metrics": ["rouge", "accuracy", "bleu"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:24:47+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: yuvraj/summarizer-cnndm
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: yuvraj/summarizer-cnndm\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: yuvraj/summarizer-cnndm\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
13,
90,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: yuvraj/summarizer-cnndm\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @URL for evaluating this model."
] |
f6a6875b67b9ca3680de466998d985c496e2b496
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@https://huggingface.co/Sini](https://huggingface.co/https://huggingface.co/Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-6c534f-38130145045
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:18:34+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "google/pegasus-cnn_dailymail", "metrics": ["rouge", "accuracy", "bleu"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T15:01:24+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
13,
90,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @URL for evaluating this model."
] |
9c60221e96d0b2295e5b496333f470585ef927e9
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_cnn_daily_mail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@https://huggingface.co/Sini](https://huggingface.co/https://huggingface.co/Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-6c534f-38130145046
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:18:44+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "google/roberta2roberta_L-24_cnn_daily_mail", "metrics": ["rouge", "accuracy", "bleu"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:56:37+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_cnn_daily_mail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
13,
96,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @URL for evaluating this model."
] |
03c1ce1bfc55c64235f142da57f427115f6a320a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: minhtoan/t5-finetune-cnndaily-news
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@https://huggingface.co/Sini](https://huggingface.co/https://huggingface.co/Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-6c534f-38130145047
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:18:54+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "minhtoan/t5-finetune-cnndaily-news", "metrics": ["rouge", "accuracy", "bleu"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:22:14+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: minhtoan/t5-finetune-cnndaily-news
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: minhtoan/t5-finetune-cnndaily-news\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: minhtoan/t5-finetune-cnndaily-news\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL for evaluating this model."
] |
[
13,
93,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: minhtoan/t5-finetune-cnndaily-news\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @URL for evaluating this model."
] |
98bd93dd0eca1fcdda3b8824f4672de76d55d64a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: siberett/roberta-sentiment-analysis-finetune
* Dataset: tweet_eval
* Config: sentiment
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@emuggins](https://huggingface.co/emuggins) for evaluating this model.
|
autoevaluate/autoeval-eval-tweet_eval-sentiment-45124a-38605145054
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:20:04+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["tweet_eval"], "eval_info": {"task": "multi_class_classification", "model": "siberett/roberta-sentiment-analysis-finetune", "metrics": [], "dataset_name": "tweet_eval", "dataset_config": "sentiment", "dataset_split": "train", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T13:23:31+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Multi-class Text Classification
* Model: siberett/roberta-sentiment-analysis-finetune
* Dataset: tweet_eval
* Config: sentiment
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @emuggins for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: siberett/roberta-sentiment-analysis-finetune\n* Dataset: tweet_eval\n* Config: sentiment\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @emuggins for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: siberett/roberta-sentiment-analysis-finetune\n* Dataset: tweet_eval\n* Config: sentiment\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @emuggins for evaluating this model."
] |
[
13,
95,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: siberett/roberta-sentiment-analysis-finetune\n* Dataset: tweet_eval\n* Config: sentiment\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @emuggins for evaluating this model."
] |
e50459e85673e2eac5e976fcb1c6e518db70221d
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@pszemraj](https://huggingface.co/pszemraj) for evaluating this model.
|
autoevaluate/autoeval-eval-xsum-default-98b05d-39746145061
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:21:20+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xsum"], "eval_info": {"task": "summarization", "model": "stacked-summaries/flan-t5-large-stacked-xsum-1024", "metrics": [], "dataset_name": "xsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:53:56+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @pszemraj for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
13,
95,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
36ef0321c0fb378360a45c46adc8c33426aeb4c9
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: etalab-ia/camembert-base-squadFR-fquad-piaf
* Dataset: piaf
* Config: plain_text
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-piaf-plain_text-42b979-39890145062
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:21:32+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["piaf"], "eval_info": {"task": "extractive_question_answering", "model": "etalab-ia/camembert-base-squadFR-fquad-piaf", "metrics": ["accuracy"], "dataset_name": "piaf", "dataset_config": "plain_text", "dataset_split": "train", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T13:22:35+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: etalab-ia/camembert-base-squadFR-fquad-piaf
* Dataset: piaf
* Config: plain_text
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @URL@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: etalab-ia/camembert-base-squadFR-fquad-piaf\n* Dataset: piaf\n* Config: plain_text\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: etalab-ia/camembert-base-squadFR-fquad-piaf\n* Dataset: piaf\n* Config: plain_text\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @URL@URL for evaluating this model."
] |
[
13,
97,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: etalab-ia/camembert-base-squadFR-fquad-piaf\n* Dataset: piaf\n* Config: plain_text\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @URL@URL for evaluating this model."
] |
1db105bc1ab57ac9a68e4daf98cb2ce72020f608
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@pszemraj](https://huggingface.co/pszemraj) for evaluating this model.
|
autoevaluate/autoeval-eval-xsum-default-5ccdc1-40225145066
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:22:14+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xsum"], "eval_info": {"task": "summarization", "model": "stacked-summaries/flan-t5-large-stacked-xsum-1024", "metrics": [], "dataset_name": "xsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:53:53+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @pszemraj for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
13,
95,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: stacked-summaries/flan-t5-large-stacked-xsum-1024\n* Dataset: xsum\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
c47255726d950b447d15746849440dfc38ece4ed
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Ce/bert-finetuned-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@ashwathjadhav23](https://huggingface.co/ashwathjadhav23) for evaluating this model.
|
autoevaluate/autoeval-eval-conll2003-conll2003-19d2d7-41085145069
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:22:47+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["conll2003"], "eval_info": {"task": "entity_extraction", "model": "Ce/bert-finetuned-ner", "metrics": [], "dataset_name": "conll2003", "dataset_config": "conll2003", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}}
|
2023-10-04T13:24:14+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: Ce/bert-finetuned-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @ashwathjadhav23 for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: Ce/bert-finetuned-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @ashwathjadhav23 for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: Ce/bert-finetuned-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @ashwathjadhav23 for evaluating this model."
] |
[
13,
88,
19
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: Ce/bert-finetuned-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @ashwathjadhav23 for evaluating this model."
] |
7fd9ea072037b7c07dcebb8c4853a2ad9efc5f89
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_cnn_daily_mail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Riux](https://huggingface.co/Riux) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-ce0087-41465145072
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:23:19+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "google/roberta2roberta_L-24_cnn_daily_mail", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:57:56+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_cnn_daily_mail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Riux for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
13,
96,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Riux for evaluating this model."
] |
5665dcf2e86e0d0915dbd4374581cec915591fb2
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: philschmid/bart-large-cnn-samsum
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Riux](https://huggingface.co/Riux) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-ce0087-41465145073
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:23:30+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "philschmid/bart-large-cnn-samsum", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:24:03+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: philschmid/bart-large-cnn-samsum
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Riux for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/bart-large-cnn-samsum\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/bart-large-cnn-samsum\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
13,
94,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/bart-large-cnn-samsum\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Riux for evaluating this model."
] |
0dca5ae36fd758cfca73060df60797dc4ce7ed45
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: philschmid/bart-large-cnn-samsum
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Riux](https://huggingface.co/Riux) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-d83e4c-41468145074
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:23:42+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "philschmid/bart-large-cnn-samsum", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:25:27+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: philschmid/bart-large-cnn-samsum
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Riux for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/bart-large-cnn-samsum\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/bart-large-cnn-samsum\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
13,
94,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/bart-large-cnn-samsum\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Riux for evaluating this model."
] |
e92a7549d76d408b8e5e1ec3f62e470e97135f68
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_cnn_daily_mail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Riux](https://huggingface.co/Riux) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-d83e4c-41468145075
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:23:51+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "google/roberta2roberta_L-24_cnn_daily_mail", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:58:58+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_cnn_daily_mail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Riux for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Riux for evaluating this model."
] |
[
13,
96,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_cnn_daily_mail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Riux for evaluating this model."
] |
0c6d1c3b19d5ddbde0d4d11a218e6cfe0767b77a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: achimoraites/flan-t5-base-samsum
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@achimoraites](https://huggingface.co/achimoraites) for evaluating this model.
|
autoevaluate/autoeval-eval-samsum-samsum-e62894-41756145079
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:24:31+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["samsum"], "eval_info": {"task": "summarization", "model": "achimoraites/flan-t5-base-samsum", "metrics": [], "dataset_name": "samsum", "dataset_config": "samsum", "dataset_split": "test", "col_mapping": {"text": "dialogue", "target": "summary"}}}
|
2023-10-04T13:25:40+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: achimoraites/flan-t5-base-samsum
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @achimoraites for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: achimoraites/flan-t5-base-samsum\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @achimoraites for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: achimoraites/flan-t5-base-samsum\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @achimoraites for evaluating this model."
] |
[
13,
89,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: achimoraites/flan-t5-base-samsum\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @achimoraites for evaluating this model."
] |
03a5d2a804536eeeab9329d1d57b57b1a0df7a84
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@neuromentor](https://huggingface.co/neuromentor) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-f4ef6e-41949145080
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:24:42+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ARTeLab/it5-summarization-fanpage", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:35:01+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ARTeLab/it5-summarization-fanpage
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @neuromentor for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @neuromentor for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @neuromentor for evaluating this model."
] |
[
13,
91,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ARTeLab/it5-summarization-fanpage\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @neuromentor for evaluating this model."
] |
be452dfa9aa2e9cd3a4a57c174f4cdef22838236
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ArtifactAI/led_large_16384_arxiv_summarization
* Dataset: ccdv/arxiv-summarization
* Config: section
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@ArtifactAI](https://huggingface.co/ArtifactAI) for evaluating this model.
|
autoevaluate/autoeval-eval-ccdv__arxiv-summarization-section-8d788a-42021145085
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:25:37+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["ccdv/arxiv-summarization"], "eval_info": {"task": "summarization", "model": "ArtifactAI/led_large_16384_arxiv_summarization", "metrics": [], "dataset_name": "ccdv/arxiv-summarization", "dataset_config": "section", "dataset_split": "test", "col_mapping": {"text": "article", "target": "abstract"}}}
|
2023-10-05T06:33:08+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ArtifactAI/led_large_16384_arxiv_summarization
* Dataset: ccdv/arxiv-summarization
* Config: section
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @ArtifactAI for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ArtifactAI/led_large_16384_arxiv_summarization\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @ArtifactAI for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ArtifactAI/led_large_16384_arxiv_summarization\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @ArtifactAI for evaluating this model."
] |
[
13,
103,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ArtifactAI/led_large_16384_arxiv_summarization\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @ArtifactAI for evaluating this model."
] |
8eeb2161f6203d6965b245ef3b0b1c5bafcf5f4d
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ArtifactAI/led_base_16384_arxiv_summarization
* Dataset: ccdv/arxiv-summarization
* Config: section
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@ArtifactAI](https://huggingface.co/ArtifactAI) for evaluating this model.
|
autoevaluate/autoeval-eval-ccdv__arxiv-summarization-section-c4e7c7-42022145086
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:25:48+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["ccdv/arxiv-summarization"], "eval_info": {"task": "summarization", "model": "ArtifactAI/led_base_16384_arxiv_summarization", "metrics": [], "dataset_name": "ccdv/arxiv-summarization", "dataset_config": "section", "dataset_split": "test", "col_mapping": {"text": "article", "target": "abstract"}}}
|
2023-10-04T21:36:38+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ArtifactAI/led_base_16384_arxiv_summarization
* Dataset: ccdv/arxiv-summarization
* Config: section
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @ArtifactAI for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ArtifactAI/led_base_16384_arxiv_summarization\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @ArtifactAI for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ArtifactAI/led_base_16384_arxiv_summarization\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @ArtifactAI for evaluating this model."
] |
[
13,
102,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ArtifactAI/led_base_16384_arxiv_summarization\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @ArtifactAI for evaluating this model."
] |
e47f93b07e9e3bfa609a04e7a5a7504d639f26e9
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: 123tarunanand/roberta-base-finetuned
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@izara](https://huggingface.co/izara) for evaluating this model.
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-677cfa-42096145090
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:26:30+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["adversarial_qa"], "eval_info": {"task": "extractive_question_answering", "model": "123tarunanand/roberta-base-finetuned", "metrics": ["bertscore"], "dataset_name": "adversarial_qa", "dataset_config": "adversarialQA", "dataset_split": "validation", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T13:27:20+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: 123tarunanand/roberta-base-finetuned
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @izara for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 123tarunanand/roberta-base-finetuned\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @izara for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 123tarunanand/roberta-base-finetuned\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @izara for evaluating this model."
] |
[
13,
93,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 123tarunanand/roberta-base-finetuned\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @izara for evaluating this model."
] |
dcfba7d5880d8831ae2325cef0148d02f6e6e523
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Translation
* Model: Lvxue/finetuned-mt5-small-10epoch
* Dataset: wmt16
* Config: cs-en
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@DarkSourceOfCode](https://huggingface.co/DarkSourceOfCode) for evaluating this model.
|
autoevaluate/autoeval-eval-wmt16-cs-en-ba4e67-42154145091
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:26:50+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["wmt16"], "eval_info": {"task": "translation", "model": "Lvxue/finetuned-mt5-small-10epoch", "metrics": ["bleu"], "dataset_name": "wmt16", "dataset_config": "cs-en", "dataset_split": "train", "col_mapping": {"source": "translation.cs", "target": "translation.en"}}}
|
2023-10-04T17:13:25+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Translation
* Model: Lvxue/finetuned-mt5-small-10epoch
* Dataset: wmt16
* Config: cs-en
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @DarkSourceOfCode for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: cs-en\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: cs-en\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
[
13,
94,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: cs-en\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
8bbc179b2d47ab175cf943e9585efbaa92469c17
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Translation
* Model: Lvxue/finetuned-mt5-small-10epoch
* Dataset: wmt16
* Config: cs-en
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@DarkSourceOfCode](https://huggingface.co/DarkSourceOfCode) for evaluating this model.
|
autoevaluate/autoeval-eval-wmt16-cs-en-110a70-42155145092
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:26:57+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["wmt16"], "eval_info": {"task": "translation", "model": "Lvxue/finetuned-mt5-small-10epoch", "metrics": ["accuracy"], "dataset_name": "wmt16", "dataset_config": "cs-en", "dataset_split": "train", "col_mapping": {"source": "translation.cs", "target": "translation.en"}}}
|
2023-10-04T17:11:09+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Translation
* Model: Lvxue/finetuned-mt5-small-10epoch
* Dataset: wmt16
* Config: cs-en
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @DarkSourceOfCode for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: cs-en\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: cs-en\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
[
13,
94,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: cs-en\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
76e6505a0d88ef2f17d137ba0be327a6e59a5d89
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Translation
* Model: Lvxue/finetuned-mt5-small-10epoch
* Dataset: wmt16
* Config: de-en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@DarkSourceOfCode](https://huggingface.co/DarkSourceOfCode) for evaluating this model.
|
autoevaluate/autoeval-eval-wmt16-de-en-bfa340-42157145094
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:28:14+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["wmt16"], "eval_info": {"task": "translation", "model": "Lvxue/finetuned-mt5-small-10epoch", "metrics": ["accuracy"], "dataset_name": "wmt16", "dataset_config": "de-en", "dataset_split": "test", "col_mapping": {"source": "translation.en", "target": "translation.de"}}}
|
2023-10-04T13:29:49+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Translation
* Model: Lvxue/finetuned-mt5-small-10epoch
* Dataset: wmt16
* Config: de-en
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @DarkSourceOfCode for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: de-en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: de-en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
[
13,
94,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: Lvxue/finetuned-mt5-small-10epoch\n* Dataset: wmt16\n* Config: de-en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @DarkSourceOfCode for evaluating this model."
] |
8573ee754d2d2631161438fe7e904e05a180b344
|
Куча всяких рандомных порно рассказов из интеренета, из разных тегов, но без жести.
|
ASIDS/LewdRuStoryforTrain
|
[
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:ru",
"license:mit",
"not-for-all-audiences",
"instruction-finetuning",
"region:us"
] |
2023-10-04T13:30:09+00:00
|
{"language": ["ru"], "license": "mit", "size_categories": ["1K<n<10K"], "task_categories": ["text-generation"], "pretty_name": "LewdRuStoryforTrain", "tags": ["not-for-all-audiences", "instruction-finetuning"]}
|
2023-10-05T11:06:39+00:00
|
[] |
[
"ru"
] |
TAGS
#task_categories-text-generation #size_categories-1K<n<10K #language-Russian #license-mit #not-for-all-audiences #instruction-finetuning #region-us
|
Куча всяких рандомных порно рассказов из интеренета, из разных тегов, но без жести.
|
[] |
[
"TAGS\n#task_categories-text-generation #size_categories-1K<n<10K #language-Russian #license-mit #not-for-all-audiences #instruction-finetuning #region-us \n"
] |
[
54
] |
[
"passage: TAGS\n#task_categories-text-generation #size_categories-1K<n<10K #language-Russian #license-mit #not-for-all-audiences #instruction-finetuning #region-us \n"
] |
f64cfcb1ba1d7b1c903487ff565cc3aeaf95db13
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: fabriceyhc/bert-base-uncased-imdb
* Dataset: imdb
* Config: plain_text
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@test](https://huggingface.co/test) for evaluating this model.
|
autoevaluate/autoeval-eval-imdb-plain_text-7301d6-42320145096
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:30:38+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["imdb"], "eval_info": {"task": "binary_classification", "model": "fabriceyhc/bert-base-uncased-imdb", "metrics": [], "dataset_name": "imdb", "dataset_config": "plain_text", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T13:32:55+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Binary Text Classification
* Model: fabriceyhc/bert-base-uncased-imdb
* Dataset: imdb
* Config: plain_text
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @test for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Binary Text Classification\n* Model: fabriceyhc/bert-base-uncased-imdb\n* Dataset: imdb\n* Config: plain_text\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @test for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Binary Text Classification\n* Model: fabriceyhc/bert-base-uncased-imdb\n* Dataset: imdb\n* Config: plain_text\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @test for evaluating this model."
] |
[
13,
94,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Binary Text Classification\n* Model: fabriceyhc/bert-base-uncased-imdb\n* Dataset: imdb\n* Config: plain_text\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @test for evaluating this model."
] |
830d406983d6da5f117dcc22058264a01fa93816
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: philschmid/distilbart-cnn-12-6-samsum
* Dataset: banking77
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@linaycme](https://huggingface.co/linaycme) for evaluating this model.
|
autoevaluate/autoeval-eval-banking77-default-9850b7-42924145110
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:31:51+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["banking77"], "eval_info": {"task": "summarization", "model": "philschmid/distilbart-cnn-12-6-samsum", "metrics": [], "dataset_name": "banking77", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T13:44:27+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: philschmid/distilbart-cnn-12-6-samsum
* Dataset: banking77
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @linaycme for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/distilbart-cnn-12-6-samsum\n* Dataset: banking77\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @linaycme for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/distilbart-cnn-12-6-samsum\n* Dataset: banking77\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @linaycme for evaluating this model."
] |
[
13,
92,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: philschmid/distilbart-cnn-12-6-samsum\n* Dataset: banking77\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @linaycme for evaluating this model."
] |
74dbea579bb8b080bfadb15501de55784b770f14
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jayeeap](https://huggingface.co/jayeeap) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-73237a-43943145136
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:43:12+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:18:17+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @jayeeap for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @jayeeap for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @jayeeap for evaluating this model."
] |
[
13,
105,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @jayeeap for evaluating this model."
] |
5655c5dde15320f703961240a57b5482b5421292
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: 1987kostya/distilbert-base-uncased-finetuned-squad
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Isuru0x01 ](https://huggingface.co/Isuru0x01 ) for evaluating this model.
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-6fa21e-43607145128
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:46:21+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["adversarial_qa"], "eval_info": {"task": "extractive_question_answering", "model": "1987kostya/distilbert-base-uncased-finetuned-squad", "metrics": [], "dataset_name": "adversarial_qa", "dataset_config": "adversarialQA", "dataset_split": "validation", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T13:47:16+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: 1987kostya/distilbert-base-uncased-finetuned-squad
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Isuru0x01 for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 1987kostya/distilbert-base-uncased-finetuned-squad\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Isuru0x01 for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 1987kostya/distilbert-base-uncased-finetuned-squad\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Isuru0x01 for evaluating this model."
] |
[
13,
100,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 1987kostya/distilbert-base-uncased-finetuned-squad\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Isuru0x01 for evaluating this model."
] |
939a32cf0025398c0abb47f655ca8afb8c998237
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-base
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Brez](https://huggingface.co/Brez) for evaluating this model.
|
autoevaluate/autoeval-eval-multi_news-default-6ca477-44786145148
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:46:40+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["multi_news"], "eval_info": {"task": "summarization", "model": "t5-base", "metrics": ["rouge"], "dataset_name": "multi_news", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:52:12+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: t5-base
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Brez for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Brez for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Brez for evaluating this model."
] |
[
13,
79,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Brez for evaluating this model."
] |
a0ffdbab4b3d0904aa9f47bd1a764fedc5deb5ed
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-multi_news
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Brez](https://huggingface.co/Brez) for evaluating this model.
|
autoevaluate/autoeval-eval-multi_news-default-52dcdc-44771145146
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:46:47+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["multi_news"], "eval_info": {"task": "summarization", "model": "google/pegasus-multi_news", "metrics": ["rouge"], "dataset_name": "multi_news", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T15:36:10+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-multi_news
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Brez for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-multi_news\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Brez for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-multi_news\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Brez for evaluating this model."
] |
[
13,
85,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-multi_news\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Brez for evaluating this model."
] |
e17960170287225f1f06109cad5feba91aec1d4a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: Einmalumdiewelt/T5-Base_GNAD
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@TotallyIntended](https://huggingface.co/TotallyIntended) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-af1ac4-44796145150
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:47:45+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "Einmalumdiewelt/T5-Base_GNAD", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T13:56:38+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: Einmalumdiewelt/T5-Base_GNAD
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @TotallyIntended for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Einmalumdiewelt/T5-Base_GNAD\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @TotallyIntended for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Einmalumdiewelt/T5-Base_GNAD\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @TotallyIntended for evaluating this model."
] |
[
13,
92,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Einmalumdiewelt/T5-Base_GNAD\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @TotallyIntended for evaluating this model."
] |
b53c441032130436246fb75597366e16fa040f0e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Brez](https://huggingface.co/Brez) for evaluating this model.
|
autoevaluate/autoeval-eval-multi_news-default-6ca477-44786145147
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:50:15+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["multi_news"], "eval_info": {"task": "summarization", "model": "facebook/bart-large-cnn", "metrics": ["rouge"], "dataset_name": "multi_news", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T14:15:32+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Brez for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Brez for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Brez for evaluating this model."
] |
[
13,
85,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Brez for evaluating this model."
] |
59cccf9eeda83cc93abd7741973dd585e713cc0f
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-multi_news-default-1c7825-44810145151
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:50:31+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["multi_news"], "eval_info": {"task": "summarization", "model": "facebook/bart-large-cnn", "metrics": ["rouge"], "dataset_name": "multi_news", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T14:15:36+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @1136517075@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @1136517075@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @1136517075@URL for evaluating this model."
] |
[
13,
85,
19
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @1136517075@URL for evaluating this model."
] |
193f033abf65227023d62c6101596bba217f195b
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-base
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-multi_news-default-1c7825-44810145152
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:54:26+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["multi_news"], "eval_info": {"task": "summarization", "model": "t5-base", "metrics": ["rouge"], "dataset_name": "multi_news", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}}
|
2023-10-04T13:59:52+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: t5-base
* Dataset: multi_news
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @1136517075@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @1136517075@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @1136517075@URL for evaluating this model."
] |
[
13,
79,
19
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: multi_news\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @1136517075@URL for evaluating this model."
] |
bbe45018e732e0eba2ef731c8bf09f880770f09d
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-samsum-samsum-2c8026-46001145176
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:57:51+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["samsum"], "eval_info": {"task": "summarization", "model": "facebook/bart-large-cnn", "metrics": [], "dataset_name": "samsum", "dataset_config": "samsum", "dataset_split": "test", "col_mapping": {"text": "dialogue", "target": "summary"}}}
|
2023-10-04T14:00:51+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @351263858@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @351263858@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @351263858@URL for evaluating this model."
] |
[
13,
85,
19
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @351263858@URL for evaluating this model."
] |
6f3826088040ca772ead7dea8d85ea0243fee064
|
# PubMed dataset in raw XML.
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
Once a year, NLM produces a baseline set of PubMed citation records in XML format for download; the baseline file is a complete snapshot of PubMed data. When using this data in a local database, the best practice is to overwrite your local data each year with the baseline data.
## Dataset Structure
XML
### Source Data
https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/
|
chungimungi/pubmed
|
[
"task_categories:text-classification",
"task_categories:table-question-answering",
"task_categories:token-classification",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"task_categories:feature-extraction",
"task_categories:text-generation",
"task_categories:text2text-generation",
"task_categories:sentence-similarity",
"language:en",
"medical",
"region:us"
] |
2023-10-04T13:58:22+00:00
|
{"language": ["en"], "task_categories": ["text-classification", "table-question-answering", "token-classification", "question-answering", "zero-shot-classification", "feature-extraction", "text-generation", "text2text-generation", "sentence-similarity"], "pretty_name": "y", "tags": ["medical"]}
|
2023-10-05T04:55:53+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-text-classification #task_categories-table-question-answering #task_categories-token-classification #task_categories-question-answering #task_categories-zero-shot-classification #task_categories-feature-extraction #task_categories-text-generation #task_categories-text2text-generation #task_categories-sentence-similarity #language-English #medical #region-us
|
# PubMed dataset in raw XML.
## Dataset Description
- Homepage:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:
### Dataset Summary
Once a year, NLM produces a baseline set of PubMed citation records in XML format for download; the baseline file is a complete snapshot of PubMed data. When using this data in a local database, the best practice is to overwrite your local data each year with the baseline data.
## Dataset Structure
XML
### Source Data
URL
|
[
"# PubMed dataset in raw XML.",
"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nOnce a year, NLM produces a baseline set of PubMed citation records in XML format for download; the baseline file is a complete snapshot of PubMed data. When using this data in a local database, the best practice is to overwrite your local data each year with the baseline data.",
"## Dataset Structure\nXML",
"### Source Data\nURL"
] |
[
"TAGS\n#task_categories-text-classification #task_categories-table-question-answering #task_categories-token-classification #task_categories-question-answering #task_categories-zero-shot-classification #task_categories-feature-extraction #task_categories-text-generation #task_categories-text2text-generation #task_categories-sentence-similarity #language-English #medical #region-us \n",
"# PubMed dataset in raw XML.",
"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nOnce a year, NLM produces a baseline set of PubMed citation records in XML format for download; the baseline file is a complete snapshot of PubMed data. When using this data in a local database, the best practice is to overwrite your local data each year with the baseline data.",
"## Dataset Structure\nXML",
"### Source Data\nURL"
] |
[
124,
9,
24,
72,
7,
5
] |
[
"passage: TAGS\n#task_categories-text-classification #task_categories-table-question-answering #task_categories-token-classification #task_categories-question-answering #task_categories-zero-shot-classification #task_categories-feature-extraction #task_categories-text-generation #task_categories-text2text-generation #task_categories-sentence-similarity #language-English #medical #region-us \n# PubMed dataset in raw XML.## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:### Dataset Summary\n\nOnce a year, NLM produces a baseline set of PubMed citation records in XML format for download; the baseline file is a complete snapshot of PubMed data. When using this data in a local database, the best practice is to overwrite your local data each year with the baseline data.## Dataset Structure\nXML### Source Data\nURL"
] |
e1ddb84f902b5a2d7780c425774144ab164c7e27
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@nomic-ai](https://huggingface.co/nomic-ai) for evaluating this model.
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-1b5bc0-46134145181
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:58:46+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["adversarial_qa"], "eval_info": {"task": "extractive_question_answering", "model": "andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat", "metrics": [], "dataset_name": "adversarial_qa", "dataset_config": "adversarialQA", "dataset_split": "validation", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T14:00:17+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @nomic-ai for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @nomic-ai for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @nomic-ai for evaluating this model."
] |
[
13,
122,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @nomic-ai for evaluating this model."
] |
2793140db9b25bbd0ee322309e21839478498186
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@wuhou](https://huggingface.co/wuhou) for evaluating this model.
|
autoevaluate/autoeval-eval-samsum-samsum-bc6414-46260145184
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:59:32+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["samsum"], "eval_info": {"task": "summarization", "model": "facebook/bart-large-cnn", "metrics": [], "dataset_name": "samsum", "dataset_config": "samsum", "dataset_split": "test", "col_mapping": {"text": "dialogue", "target": "summary"}}}
|
2023-10-04T14:02:36+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @wuhou for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @wuhou for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @wuhou for evaluating this model."
] |
[
13,
85,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @wuhou for evaluating this model."
] |
9c6d38a0806ab9e532cd83f2d60c7b80ba6c6dcc
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: andi611/distilbert-base-uncased-qa-boolq
* Dataset: boolq
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mabuyun](https://huggingface.co/mabuyun) for evaluating this model.
|
autoevaluate/autoeval-eval-boolq-default-cb11e4-46279145185
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T13:59:38+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["boolq"], "eval_info": {"task": "natural_language_inference", "model": "andi611/distilbert-base-uncased-qa-boolq", "metrics": [], "dataset_name": "boolq", "dataset_config": "default", "dataset_split": "train", "col_mapping": {"text1": "passage", "text2": "question", "target": "answer"}}}
|
2023-10-04T14:00:20+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Natural Language Inference
* Model: andi611/distilbert-base-uncased-qa-boolq
* Dataset: boolq
* Config: default
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @mabuyun for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Natural Language Inference\n* Model: andi611/distilbert-base-uncased-qa-boolq\n* Dataset: boolq\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @mabuyun for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Natural Language Inference\n* Model: andi611/distilbert-base-uncased-qa-boolq\n* Dataset: boolq\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @mabuyun for evaluating this model."
] |
[
13,
96,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Natural Language Inference\n* Model: andi611/distilbert-base-uncased-qa-boolq\n* Dataset: boolq\n* Config: default\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @mabuyun for evaluating this model."
] |
6a1654119b7e4a1446fa96609e78a7d0a17b7f90
|
[Baize](https://github.com/project-baize/baize-chatbot) has scrapped questions from Quora. The dialogs are generated by letting ChatGPT chat with itself.
This dataset is in alpaca format.
|
twodgirl/baize-quora
|
[
"language:en",
"license:gpl-3.0",
"quora",
"region:us"
] |
2023-10-04T14:03:11+00:00
|
{"language": ["en"], "license": "gpl-3.0", "tags": ["quora"]}
|
2023-10-04T15:17:31+00:00
|
[] |
[
"en"
] |
TAGS
#language-English #license-gpl-3.0 #quora #region-us
|
Baize has scrapped questions from Quora. The dialogs are generated by letting ChatGPT chat with itself.
This dataset is in alpaca format.
|
[] |
[
"TAGS\n#language-English #license-gpl-3.0 #quora #region-us \n"
] |
[
21
] |
[
"passage: TAGS\n#language-English #license-gpl-3.0 #quora #region-us \n"
] |
64cdc463da66470577fbb8570bc5ea31ebb90eea
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Translation
* Model: chence08/mt5-small-iwslt2017-zh-en
* Dataset: iwslt2017
* Config: iwslt2017-zh-en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@chence08](https://huggingface.co/chence08) for evaluating this model.
|
autoevaluate/autoeval-eval-iwslt2017-iwslt2017-zh-en-cdea8b-47199145201
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:03:49+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["iwslt2017"], "eval_info": {"task": "translation", "model": "chence08/mt5-small-iwslt2017-zh-en", "metrics": [], "dataset_name": "iwslt2017", "dataset_config": "iwslt2017-zh-en", "dataset_split": "test", "col_mapping": {"source": "translation.en", "target": "translation.zh"}}}
|
2023-10-04T14:31:49+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Translation
* Model: chence08/mt5-small-iwslt2017-zh-en
* Dataset: iwslt2017
* Config: iwslt2017-zh-en
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @chence08 for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: chence08/mt5-small-iwslt2017-zh-en\n* Dataset: iwslt2017\n* Config: iwslt2017-zh-en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @chence08 for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: chence08/mt5-small-iwslt2017-zh-en\n* Dataset: iwslt2017\n* Config: iwslt2017-zh-en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @chence08 for evaluating this model."
] |
[
13,
100,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Translation\n* Model: chence08/mt5-small-iwslt2017-zh-en\n* Dataset: iwslt2017\n* Config: iwslt2017-zh-en\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @chence08 for evaluating this model."
] |
fcf4830863be8faad62f591f7b94947047430479
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: cointegrated/rut5-base-absum
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@d0rj](https://huggingface.co/d0rj) for evaluating this model.
|
autoevaluate/autoeval-eval-samsum-samsum-e2a688-46336145186
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:04:11+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["samsum"], "eval_info": {"task": "summarization", "model": "cointegrated/rut5-base-absum", "metrics": [], "dataset_name": "samsum", "dataset_config": "samsum", "dataset_split": "test", "col_mapping": {"text": "dialogue", "target": "summary"}}}
|
2023-10-04T14:05:20+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: cointegrated/rut5-base-absum
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @d0rj for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: cointegrated/rut5-base-absum\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @d0rj for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: cointegrated/rut5-base-absum\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @d0rj for evaluating this model."
] |
[
13,
86,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: cointegrated/rut5-base-absum\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @d0rj for evaluating this model."
] |
b7caf2f20fb8ce6898bd05928e5c36783bd3c737
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: avioo1/distilbert-base-uncased-finetuned-squad
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@melodyeee](https://huggingface.co/melodyeee) for evaluating this model.
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-2b4cb4-47225145203
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:04:22+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["adversarial_qa"], "eval_info": {"task": "extractive_question_answering", "model": "avioo1/distilbert-base-uncased-finetuned-squad", "metrics": [], "dataset_name": "adversarial_qa", "dataset_config": "adversarialQA", "dataset_split": "validation", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T14:05:17+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: avioo1/distilbert-base-uncased-finetuned-squad
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @melodyeee for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: avioo1/distilbert-base-uncased-finetuned-squad\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @melodyeee for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: avioo1/distilbert-base-uncased-finetuned-squad\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @melodyeee for evaluating this model."
] |
[
13,
99,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: avioo1/distilbert-base-uncased-finetuned-squad\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @melodyeee for evaluating this model."
] |
0854d9a4551096bf84b2a2c4927f0fccdfbd0790
|
# Dataset Card for "dialogue_instruction_with_reward_score_judged_by_13B_llama2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
DialogueCharacter/english_dialogue_instruction_with_reward_score_judged_by_13B_llama2
|
[
"region:us"
] |
2023-10-04T14:06:25+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}, {"name": "reward_score", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 888623949, "num_examples": 909740}], "download_size": 475765484, "dataset_size": 888623949}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]}
|
2023-10-29T03:54:07+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "dialogue_instruction_with_reward_score_judged_by_13B_llama2"
More Information needed
|
[
"# Dataset Card for \"dialogue_instruction_with_reward_score_judged_by_13B_llama2\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"dialogue_instruction_with_reward_score_judged_by_13B_llama2\"\n\nMore Information needed"
] |
[
6,
36
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"dialogue_instruction_with_reward_score_judged_by_13B_llama2\"\n\nMore Information needed"
] |
e0286a3349ab9a961b8bda569475af157b700cf4
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-large
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sohamchougule](https://huggingface.co/sohamchougule) for evaluating this model.
|
autoevaluate/autoeval-eval-samsum-samsum-2d4eb1-47303145208
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:07:24+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["samsum"], "eval_info": {"task": "summarization", "model": "google/pegasus-large", "metrics": [], "dataset_name": "samsum", "dataset_config": "samsum", "dataset_split": "test", "col_mapping": {"text": "dialogue", "target": "summary"}}}
|
2023-10-04T14:14:34+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-large
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @sohamchougule for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-large\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sohamchougule for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-large\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sohamchougule for evaluating this model."
] |
[
13,
84,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-large\n* Dataset: samsum\n* Config: samsum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @sohamchougule for evaluating this model."
] |
5ac5102b116791144ea6b899feba2fc93ba53121
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: kworts/BARTxiv
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Raj P Sini](https://huggingface.co/Raj P Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-52cdb7-47832145225
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:09:41+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "kworts/BARTxiv", "metrics": ["accuracy", "rouge", "mse"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T15:15:42+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: kworts/BARTxiv
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Raj P Sini for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: kworts/BARTxiv\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: kworts/BARTxiv\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
13,
87,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: kworts/BARTxiv\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
9d166dec9ce946b0549ee55005a7d0bc5aecf011
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: flax-community/t5-base-cnn-dm
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Raj P Sini](https://huggingface.co/Raj P Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-52cdb7-47832145227
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:09:46+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "flax-community/t5-base-cnn-dm", "metrics": ["accuracy", "rouge", "mse"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:18:33+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: flax-community/t5-base-cnn-dm
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Raj P Sini for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: flax-community/t5-base-cnn-dm\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: flax-community/t5-base-cnn-dm\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
13,
95,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: flax-community/t5-base-cnn-dm\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
6ee61ad3a816f95ce32147e7074d5df3d5a38c28
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Raj P Sini](https://huggingface.co/Raj P Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-52cdb7-47832145229
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:10:36+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "google/pegasus-cnn_dailymail", "metrics": ["accuracy", "rouge", "mse"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T15:52:24+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Raj P Sini for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
13,
90,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
3b6e3f8dc2f510120b2f0fa50aa024094cb34ca1
|
# Bangumi Image Base of Horimiya
This is the image base of bangumi Horimiya, we detected 25 characters, 1848 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 233 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 90 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 69 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 40 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 109 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 162 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 20 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 36 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 31 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 180 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 48 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 69 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 21 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 20 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 12 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 131 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 72 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 26 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 38 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 24 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 190 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 8 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 18 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 77 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 124 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
BangumiBase/horimiya
|
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] |
2023-10-04T14:11:46+00:00
|
{"license": "mit", "size_categories": ["1K<n<10K"], "tags": ["art"]}
|
2023-10-04T15:15:15+00:00
|
[] |
[] |
TAGS
#size_categories-1K<n<10K #license-mit #art #region-us
|
Bangumi Image Base of Horimiya
==============================
This is the image base of bangumi Horimiya, we detected 25 characters, 1848 images in total. The full dataset is here.
Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
|
[] |
[
"TAGS\n#size_categories-1K<n<10K #license-mit #art #region-us \n"
] |
[
25
] |
[
"passage: TAGS\n#size_categories-1K<n<10K #license-mit #art #region-us \n"
] |
257cd1fc907fd34378644b3bd2980ccbd094e83d
|
# Bangumi Image Base of Chainsaw Man
This is the image base of bangumi Chainsaw Man, we detected 16 characters, 1264 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 280 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 24 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 33 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 196 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 111 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 38 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 90 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 52 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 36 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 53 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 16 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 102 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 108 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 7 | [Download](13/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 14 | 36 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 82 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
BangumiBase/chainsawman
|
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] |
2023-10-04T14:12:59+00:00
|
{"license": "mit", "size_categories": ["1K<n<10K"], "tags": ["art"]}
|
2023-10-04T15:15:05+00:00
|
[] |
[] |
TAGS
#size_categories-1K<n<10K #license-mit #art #region-us
|
Bangumi Image Base of Chainsaw Man
==================================
This is the image base of bangumi Chainsaw Man, we detected 16 characters, 1264 images in total. The full dataset is here.
Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
|
[] |
[
"TAGS\n#size_categories-1K<n<10K #license-mit #art #region-us \n"
] |
[
25
] |
[
"passage: TAGS\n#size_categories-1K<n<10K #license-mit #art #region-us \n"
] |
faa0feeb6bbc9a76c7f814d8cf173f769354c37d
|
This is dataset contain (78k samples) of the excellent [b-mc2/sql-create-context](https://huggingface.co/datasets/b-mc2/sql-create-context/viewer/default/train) and changed to [derekiya/sql-create-context-llama2-78k](https://huggingface.co/datasets/derekiya/sql-create-context-llama2-78k/viewer/default/train) dataset,
processed to match Llama 2's prompt format as described in this article.
Useful if you don't want to reformat it by yourself (e.g., using a script). It was designed for this article about fine-tuning a Llama 2 (chat)
|
derekiya/sql-create-context-llama2-78k
|
[
"region:us"
] |
2023-10-04T14:13:55+00:00
|
{}
|
2023-10-04T23:03:58+00:00
|
[] |
[] |
TAGS
#region-us
|
This is dataset contain (78k samples) of the excellent b-mc2/sql-create-context and changed to derekiya/sql-create-context-llama2-78k dataset,
processed to match Llama 2's prompt format as described in this article.
Useful if you don't want to reformat it by yourself (e.g., using a script). It was designed for this article about fine-tuning a Llama 2 (chat)
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
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[
"passage: TAGS\n#region-us \n"
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7d1a028a84df7344eafe3a7ba4c581fe26dcfd72
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed]
|
Duongkum999/duong
|
[
"license:mit",
"region:us"
] |
2023-10-04T14:14:23+00:00
|
{"license": "mit"}
|
2023-10-04T14:15:07+00:00
|
[] |
[] |
TAGS
#license-mit #region-us
|
# Dataset Card for Dataset Name
## Dataset Description
- Homepage:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### Annotation process
#### Who are the annotators?
### Personal and Sensitive Information
## Considerations for Using the Data
### Social Impact of Dataset
### Discussion of Biases
### Other Known Limitations
## Additional Information
### Dataset Curators
### Licensing Information
### Contributions
|
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012c385491403bc1dc61382dced95e93c1eec72e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-base-16384-booksci-summary-v1
* Dataset: kmfoda/booksum
* Config: kmfoda--booksum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@pszemraj](https://huggingface.co/pszemraj) for evaluating this model.
|
autoevaluate/autoeval-eval-kmfoda__booksum-kmfoda__booksum-9f206e-47938145232
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:15:05+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["kmfoda/booksum"], "eval_info": {"task": "summarization", "model": "pszemraj/long-t5-tglobal-base-16384-booksci-summary-v1", "metrics": [], "dataset_name": "kmfoda/booksum", "dataset_config": "kmfoda--booksum", "dataset_split": "test", "col_mapping": {"text": "chapter", "target": "summary_text"}}}
|
2023-10-05T00:08:44+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-base-16384-booksci-summary-v1
* Dataset: kmfoda/booksum
* Config: kmfoda--booksum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @pszemraj for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: pszemraj/long-t5-tglobal-base-16384-booksci-summary-v1\n* Dataset: kmfoda/booksum\n* Config: kmfoda--booksum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: pszemraj/long-t5-tglobal-base-16384-booksci-summary-v1\n* Dataset: kmfoda/booksum\n* Config: kmfoda--booksum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
13,
108,
16
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[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: pszemraj/long-t5-tglobal-base-16384-booksci-summary-v1\n* Dataset: kmfoda/booksum\n* Config: kmfoda--booksum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
47df88de605e7433697d1258062f62b809895644
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: adityashukzy/bart-base-new-finetuned-arxiv
* Dataset: ccdv/arxiv-summarization
* Config: section
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@adityashukzy](https://huggingface.co/adityashukzy) for evaluating this model.
|
autoevaluate/autoeval-eval-ccdv__arxiv-summarization-section-002db0-47978145233
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:15:07+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["ccdv/arxiv-summarization"], "eval_info": {"task": "summarization", "model": "adityashukzy/bart-base-new-finetuned-arxiv", "metrics": [], "dataset_name": "ccdv/arxiv-summarization", "dataset_config": "section", "dataset_split": "validation", "col_mapping": {"text": "article", "target": "abstract"}}}
|
2023-10-04T14:22:46+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: adityashukzy/bart-base-new-finetuned-arxiv
* Dataset: ccdv/arxiv-summarization
* Config: section
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @adityashukzy for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: adityashukzy/bart-base-new-finetuned-arxiv\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @adityashukzy for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: adityashukzy/bart-base-new-finetuned-arxiv\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @adityashukzy for evaluating this model."
] |
[
13,
104,
18
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[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: adityashukzy/bart-base-new-finetuned-arxiv\n* Dataset: ccdv/arxiv-summarization\n* Config: section\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @adityashukzy for evaluating this model."
] |
2e3e412b29e91ec57762f480dea6289334784417
|
# Dataset Card for "spotlight-emodb-enrichment"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
renumics/spotlight-emodb-enrichment
|
[
"region:us"
] |
2023-10-04T14:15:18+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}], "dataset_info": {"features": [{"name": "audio.embedding", "sequence": "float32", "length": 2}], "splits": [{"name": "train", "num_bytes": 4280, "num_examples": 535}], "download_size": 6880, "dataset_size": 4280}}
|
2023-10-13T08:24:05+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "spotlight-emodb-enrichment"
More Information needed
|
[
"# Dataset Card for \"spotlight-emodb-enrichment\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"spotlight-emodb-enrichment\"\n\nMore Information needed"
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[
6,
19
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"passage: TAGS\n#region-us \n# Dataset Card for \"spotlight-emodb-enrichment\"\n\nMore Information needed"
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ae51230e78609cdfca43faa43414a990bf70fd69
|
# Dataset Card for "ko_f_1871"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
ttagu99/ko_f_1871
|
[
"region:us"
] |
2023-10-04T14:15:21+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}, {"name": "instruction", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 6462525, "num_examples": 1871}], "download_size": 3201114, "dataset_size": 6462525}}
|
2023-10-04T14:15:26+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "ko_f_1871"
More Information needed
|
[
"# Dataset Card for \"ko_f_1871\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"ko_f_1871\"\n\nMore Information needed"
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[
6,
16
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[
"passage: TAGS\n#region-us \n# Dataset Card for \"ko_f_1871\"\n\nMore Information needed"
] |
71e84ee4b5e9bcba42a103ce32e7b27471b3467e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ainize/bart-base-cnn
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Raj P Sini](https://huggingface.co/Raj P Sini) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-52cdb7-47832145226
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:16:05+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ainize/bart-base-cnn", "metrics": ["accuracy", "rouge", "mse"], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:25:06+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ainize/bart-base-cnn
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Raj P Sini for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ainize/bart-base-cnn\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ainize/bart-base-cnn\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
[
13,
88,
18
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ainize/bart-base-cnn\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Raj P Sini for evaluating this model."
] |
ac03fff7ba255f0db2d141763af1415dec86093f
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: alvarobartt/distilbert-base-cased-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@alvarobartt](https://huggingface.co/alvarobartt) for evaluating this model.
|
autoevaluate/autoeval-eval-conll2003-conll2003-ce0414-48015145234
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:16:09+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["conll2003"], "eval_info": {"task": "entity_extraction", "model": "alvarobartt/distilbert-base-cased-ner", "metrics": [], "dataset_name": "conll2003", "dataset_config": "conll2003", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}}
|
2023-10-04T14:17:27+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: alvarobartt/distilbert-base-cased-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @alvarobartt for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
[
13,
94,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
4cdc279f040b6a79cfaf47f3a57cd2166decf9f8
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: alvarobartt/distilbert-base-cased-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@alvarobartt](https://huggingface.co/alvarobartt) for evaluating this model.
|
autoevaluate/autoeval-eval-conll2003-conll2003-b4bc7c-48084145235
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:17:33+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["conll2003"], "eval_info": {"task": "entity_extraction", "model": "alvarobartt/distilbert-base-cased-ner", "metrics": [], "dataset_name": "conll2003", "dataset_config": "conll2003", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}}
|
2023-10-04T14:18:51+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: alvarobartt/distilbert-base-cased-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @alvarobartt for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
[
13,
94,
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[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
a11787bea5b464e076a9d7e70cec90d636010b47
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/led-large-book-summary-continued
* Dataset: kmfoda/booksum
* Config: kmfoda--booksum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@pszemraj](https://huggingface.co/pszemraj) for evaluating this model.
|
autoevaluate/autoeval-eval-kmfoda__booksum-kmfoda__booksum-9f206e-47938145231
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:19:34+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["kmfoda/booksum"], "eval_info": {"task": "summarization", "model": "pszemraj/led-large-book-summary-continued", "metrics": [], "dataset_name": "kmfoda/booksum", "dataset_config": "kmfoda--booksum", "dataset_split": "test", "col_mapping": {"text": "chapter", "target": "summary_text"}}}
|
2023-10-04T21:46:10+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: pszemraj/led-large-book-summary-continued
* Dataset: kmfoda/booksum
* Config: kmfoda--booksum
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @pszemraj for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: pszemraj/led-large-book-summary-continued\n* Dataset: kmfoda/booksum\n* Config: kmfoda--booksum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: pszemraj/led-large-book-summary-continued\n* Dataset: kmfoda/booksum\n* Config: kmfoda--booksum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
[
13,
101,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: pszemraj/led-large-book-summary-continued\n* Dataset: kmfoda/booksum\n* Config: kmfoda--booksum\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @pszemraj for evaluating this model."
] |
194191c8952404e29136f0c9c6ffb83edc4b38ec
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: ahmedrachid/FinancialBERT-Sentiment-Analysis
* Dataset: financial_phrasebank
* Config: sentences_allagree
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@du](https://huggingface.co/du) for evaluating this model.
|
autoevaluate/autoeval-eval-financial_phrasebank-sentences_allagree-c1bf87-48200145240
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:19:53+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["financial_phrasebank"], "eval_info": {"task": "multi_class_classification", "model": "ahmedrachid/FinancialBERT-Sentiment-Analysis", "metrics": ["bleu", "google_bleu"], "dataset_name": "financial_phrasebank", "dataset_config": "sentences_allagree", "dataset_split": "train", "col_mapping": {"text": "sentence", "target": "label"}}}
|
2023-10-04T14:20:20+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Multi-class Text Classification
* Model: ahmedrachid/FinancialBERT-Sentiment-Analysis
* Dataset: financial_phrasebank
* Config: sentences_allagree
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @du for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: ahmedrachid/FinancialBERT-Sentiment-Analysis\n* Dataset: financial_phrasebank\n* Config: sentences_allagree\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @du for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: ahmedrachid/FinancialBERT-Sentiment-Analysis\n* Dataset: financial_phrasebank\n* Config: sentences_allagree\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @du for evaluating this model."
] |
[
13,
103,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: ahmedrachid/FinancialBERT-Sentiment-Analysis\n* Dataset: financial_phrasebank\n* Config: sentences_allagree\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @du for evaluating this model."
] |
afa7ddbc8fc3e68f34c38e6dab8ce4366fa2d02a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: csebuetnlp/mT5_m2o_arabic_crossSum
* Dataset: xglue
* Config: mlqa
* Split: test.ar
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Anwaarma](https://huggingface.co/Anwaarma) for evaluating this model.
|
autoevaluate/autoeval-eval-xglue-mlqa-a70280-48375145242
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:20:26+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xglue"], "eval_info": {"task": "summarization", "model": "csebuetnlp/mT5_m2o_arabic_crossSum", "metrics": ["bleu", "f1", "accuracy"], "dataset_name": "xglue", "dataset_config": "mlqa", "dataset_split": "test.ar", "col_mapping": {"text": "context", "target": "question"}}}
|
2023-10-04T14:38:23+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: csebuetnlp/mT5_m2o_arabic_crossSum
* Dataset: xglue
* Config: mlqa
* Split: URL
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Anwaarma for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: csebuetnlp/mT5_m2o_arabic_crossSum\n* Dataset: xglue\n* Config: mlqa\n* Split: URL\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Anwaarma for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: csebuetnlp/mT5_m2o_arabic_crossSum\n* Dataset: xglue\n* Config: mlqa\n* Split: URL\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Anwaarma for evaluating this model."
] |
[
13,
98,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: csebuetnlp/mT5_m2o_arabic_crossSum\n* Dataset: xglue\n* Config: mlqa\n* Split: URL\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Anwaarma for evaluating this model."
] |
242ae9fb4a5a513b8448d669590fa5304199f209
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_bbc
* Dataset: xglue
* Config: mlqa
* Split: test.ar
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Anwaarma](https://huggingface.co/Anwaarma) for evaluating this model.
|
autoevaluate/autoeval-eval-xglue-mlqa-02a2ef-48376145243
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:20:39+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["xglue"], "eval_info": {"task": "summarization", "model": "google/roberta2roberta_L-24_bbc", "metrics": ["bleu", "f1", "accuracy"], "dataset_name": "xglue", "dataset_config": "mlqa", "dataset_split": "test.ar", "col_mapping": {"text": "context", "target": "question"}}}
|
2023-10-04T14:48:14+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: google/roberta2roberta_L-24_bbc
* Dataset: xglue
* Config: mlqa
* Split: URL
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @Anwaarma for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_bbc\n* Dataset: xglue\n* Config: mlqa\n* Split: URL\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Anwaarma for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_bbc\n* Dataset: xglue\n* Config: mlqa\n* Split: URL\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @Anwaarma for evaluating this model."
] |
[
13,
90,
16
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: google/roberta2roberta_L-24_bbc\n* Dataset: xglue\n* Config: mlqa\n* Split: URL\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @Anwaarma for evaluating this model."
] |
4922b9e69d88ce995c0307db34b72edceb541cf5
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: 123tarunanand/roberta-base-finetuned
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sysneedtolearn](https://huggingface.co/sysneedtolearn) for evaluating this model.
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-f2f24c-49139145269
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:27:44+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["adversarial_qa"], "eval_info": {"task": "extractive_question_answering", "model": "123tarunanand/roberta-base-finetuned", "metrics": ["bleu", "accuracy", "angelina-wang/directional_bias_amplification", "bertscore", "rouge", "meteor"], "dataset_name": "adversarial_qa", "dataset_config": "adversarialQA", "dataset_split": "validation", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T14:28:36+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: 123tarunanand/roberta-base-finetuned
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @sysneedtolearn for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 123tarunanand/roberta-base-finetuned\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sysneedtolearn for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 123tarunanand/roberta-base-finetuned\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @sysneedtolearn for evaluating this model."
] |
[
13,
93,
20
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: 123tarunanand/roberta-base-finetuned\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @sysneedtolearn for evaluating this model."
] |
b2ab1b4675a50dd83bd7b62e6017f56d75bf50b6
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: alvarobartt/distilbert-base-cased-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@alvarobartt](https://huggingface.co/alvarobartt) for evaluating this model.
|
autoevaluate/autoeval-eval-conll2003-conll2003-fb14e9-48103145236
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:28:13+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["conll2003"], "eval_info": {"task": "entity_extraction", "model": "alvarobartt/distilbert-base-cased-ner", "metrics": [], "dataset_name": "conll2003", "dataset_config": "conll2003", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}}
|
2023-10-04T14:29:27+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: alvarobartt/distilbert-base-cased-ner
* Dataset: conll2003
* Config: conll2003
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @alvarobartt for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
[
13,
94,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: alvarobartt/distilbert-base-cased-ner\n* Dataset: conll2003\n* Config: conll2003\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @alvarobartt for evaluating this model."
] |
cfdf30c9a462cf3ecd227e6d1f19a31b6685bbb1
|
# Dataset Card for "med_leaves"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
purabp1249/med_leaves
|
[
"region:us"
] |
2023-10-04T14:34:46+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}], "dataset_info": {"features": [{"name": "file_paths", "dtype": "string"}, {"name": "image_bytes", "dtype": "binary"}, {"name": "labels", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 10878937089, "num_examples": 21880}], "download_size": 970048876, "dataset_size": 10878937089}}
|
2023-10-04T15:40:02+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "med_leaves"
More Information needed
|
[
"# Dataset Card for \"med_leaves\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"med_leaves\"\n\nMore Information needed"
] |
[
6,
14
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"med_leaves\"\n\nMore Information needed"
] |
675340bfa1b39d2e7fe0277d904f9ae2d41bd89a
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-acronym_identification-default-9ff9c1-50406145297
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:35:19+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["acronym_identification"], "eval_info": {"task": "entity_extraction", "model": "lewtun/autotrain-acronym-identification-7324788", "metrics": ["bertscore"], "dataset_name": "acronym_identification", "dataset_config": "default", "dataset_split": "validation", "col_mapping": {"tokens": "tokens", "tags": "labels"}}}
|
2023-10-04T14:35:59+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Token Classification
* Model: lewtun/autotrain-acronym-identification-7324788
* Dataset: acronym_identification
* Config: default
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @prashanthr025@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @prashanthr025@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @prashanthr025@URL for evaluating this model."
] |
[
13,
97,
20
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Token Classification\n* Model: lewtun/autotrain-acronym-identification-7324788\n* Dataset: acronym_identification\n* Config: default\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @prashanthr025@URL for evaluating this model."
] |
659723e3f30be21c79fb9a654ae984a908a81fc9
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: sambydlo/scientific_abstract_simplification-scientific-lay-summarise
* Dataset: scientific_papers
* Config: pubmed
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@NessTechIntl](https://huggingface.co/NessTechIntl) for evaluating this model.
|
autoevaluate/autoeval-eval-scientific_papers-pubmed-c3b6df-51381145312
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:36:27+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["scientific_papers"], "eval_info": {"task": "summarization", "model": "sambydlo/scientific_abstract_simplification-scientific-lay-summarise", "metrics": ["accuracy", "frugalscore"], "dataset_name": "scientific_papers", "dataset_config": "pubmed", "dataset_split": "train", "col_mapping": {"text": "article", "target": "abstract"}}}
|
2023-10-04T21:34:01+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: sambydlo/scientific_abstract_simplification-scientific-lay-summarise
* Dataset: scientific_papers
* Config: pubmed
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @NessTechIntl for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: sambydlo/scientific_abstract_simplification-scientific-lay-summarise\n* Dataset: scientific_papers\n* Config: pubmed\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @NessTechIntl for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: sambydlo/scientific_abstract_simplification-scientific-lay-summarise\n* Dataset: scientific_papers\n* Config: pubmed\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @NessTechIntl for evaluating this model."
] |
[
13,
102,
20
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: sambydlo/scientific_abstract_simplification-scientific-lay-summarise\n* Dataset: scientific_papers\n* Config: pubmed\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @NessTechIntl for evaluating this model."
] |
8028b252fde652a70c46b8db2ba16c450db7a9d4
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2
* Dataset: scientific_papers
* Config: pubmed
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@NessTechIntl](https://huggingface.co/NessTechIntl) for evaluating this model.
|
autoevaluate/autoeval-eval-scientific_papers-pubmed-c3b6df-51381145313
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:36:28+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["scientific_papers"], "eval_info": {"task": "summarization", "model": "Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2", "metrics": ["accuracy", "frugalscore"], "dataset_name": "scientific_papers", "dataset_config": "pubmed", "dataset_split": "train", "col_mapping": {"text": "article", "target": "abstract"}}}
|
2023-10-06T03:45:27+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2
* Dataset: scientific_papers
* Config: pubmed
* Split: train
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @NessTechIntl for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2\n* Dataset: scientific_papers\n* Config: pubmed\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @NessTechIntl for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2\n* Dataset: scientific_papers\n* Config: pubmed\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @NessTechIntl for evaluating this model."
] |
[
13,
104,
20
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2\n* Dataset: scientific_papers\n* Config: pubmed\n* Split: train\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @NessTechIntl for evaluating this model."
] |
9f4e06f519fc8cb26a00a034bae9f528da3e736b
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Laurie/bert-base-banking77-pt2
* Dataset: banking77
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-banking77-default-080492-51746145316
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:37:09+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["banking77"], "eval_info": {"task": "multi_class_classification", "model": "Laurie/bert-base-banking77-pt2", "metrics": [], "dataset_name": "banking77", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T14:37:51+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Laurie/bert-base-banking77-pt2
* Dataset: banking77
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @edcody726ai@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Laurie/bert-base-banking77-pt2\n* Dataset: banking77\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @edcody726ai@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Laurie/bert-base-banking77-pt2\n* Dataset: banking77\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @edcody726ai@URL for evaluating this model."
] |
[
13,
92,
21
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Laurie/bert-base-banking77-pt2\n* Dataset: banking77\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @edcody726ai@URL for evaluating this model."
] |
12990881681610aa1b1938d985b1d4b78a7d5134
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Laurie/bert-base-banking77-pt2
* Dataset: banking77
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@[email protected]](https://huggingface.co/[email protected]) for evaluating this model.
|
autoevaluate/autoeval-eval-banking77-default-2a251d-51750145317
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:37:36+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["banking77"], "eval_info": {"task": "multi_class_classification", "model": "Laurie/bert-base-banking77-pt2", "metrics": ["rouge"], "dataset_name": "banking77", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}}
|
2023-10-04T14:38:06+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Laurie/bert-base-banking77-pt2
* Dataset: banking77
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @edcody726ai@URL for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Laurie/bert-base-banking77-pt2\n* Dataset: banking77\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @edcody726ai@URL for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Laurie/bert-base-banking77-pt2\n* Dataset: banking77\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @edcody726ai@URL for evaluating this model."
] |
[
13,
92,
21
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Multi-class Text Classification\n* Model: Laurie/bert-base-banking77-pt2\n* Dataset: banking77\n* Config: default\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @edcody726ai@URL for evaluating this model."
] |
1ae2f6776f23521073466084bb65e0388b035bb9
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0x70DA/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@km](https://huggingface.co/km) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-90e029-50827145304
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:38:35+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "0x70DA/pegasus-cnn_dailymail", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T16:14:41+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: 0x70DA/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @km for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0x70DA/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @km for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0x70DA/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @km for evaluating this model."
] |
[
13,
93,
14
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: 0x70DA/pegasus-cnn_dailymail\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @km for evaluating this model."
] |
d0121ceeff9c383400fed36ad5632c1c11018863
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: zhangfx7/deberta-base-finetuned-squad-pruned0.1
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@tp](https://huggingface.co/tp) for evaluating this model.
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-0e2388-51771145321
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:38:44+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["adversarial_qa"], "eval_info": {"task": "extractive_question_answering", "model": "zhangfx7/deberta-base-finetuned-squad-pruned0.1", "metrics": [], "dataset_name": "adversarial_qa", "dataset_config": "adversarialQA", "dataset_split": "validation", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}}
|
2023-10-04T14:39:54+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Question Answering
* Model: zhangfx7/deberta-base-finetuned-squad-pruned0.1
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @tp for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: zhangfx7/deberta-base-finetuned-squad-pruned0.1\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @tp for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: zhangfx7/deberta-base-finetuned-squad-pruned0.1\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @tp for evaluating this model."
] |
[
13,
102,
15
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Question Answering\n* Model: zhangfx7/deberta-base-finetuned-squad-pruned0.1\n* Dataset: adversarial_qa\n* Config: adversarialQA\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @tp for evaluating this model."
] |
99f640b384f4ebe543ee96ee4314c0b77f38d27e
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: t5-base
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@MaryYarova](https://huggingface.co/MaryYarova) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-c51db7-51930145325
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:39:32+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "t5-base", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:47:59+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: t5-base
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @MaryYarova for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @MaryYarova for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @MaryYarova for evaluating this model."
] |
[
13,
82,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: t5-base\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @MaryYarova for evaluating this model."
] |
e66cf5a2323c8ae8f830ec7b6eb6c330f79234c9
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ubikpt/t5-small-finetuned-cnn
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@MaryYarova](https://huggingface.co/MaryYarova) for evaluating this model.
|
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-c51db7-51930145326
|
[
"autotrain",
"evaluation",
"region:us"
] |
2023-10-04T14:39:35+00:00
|
{"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["cnn_dailymail"], "eval_info": {"task": "summarization", "model": "ubikpt/t5-small-finetuned-cnn", "metrics": [], "dataset_name": "cnn_dailymail", "dataset_config": "3.0.0", "dataset_split": "test", "col_mapping": {"text": "article", "target": "highlights"}}}
|
2023-10-04T14:42:50+00:00
|
[] |
[] |
TAGS
#autotrain #evaluation #region-us
|
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: ubikpt/t5-small-finetuned-cnn
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's automatic model evaluator.
## Contributions
Thanks to @MaryYarova for evaluating this model.
|
[
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ubikpt/t5-small-finetuned-cnn\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @MaryYarova for evaluating this model."
] |
[
"TAGS\n#autotrain #evaluation #region-us \n",
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ubikpt/t5-small-finetuned-cnn\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.",
"## Contributions\n\nThanks to @MaryYarova for evaluating this model."
] |
[
13,
94,
17
] |
[
"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: ubikpt/t5-small-finetuned-cnn\n* Dataset: cnn_dailymail\n* Config: 3.0.0\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.## Contributions\n\nThanks to @MaryYarova for evaluating this model."
] |
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