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d314e754d62f7c2658898ef620b385b117a6dfa2 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-560m
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-b48d12-2175169955 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T04:36:25+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-560m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T04:55:05+00:00 |
e37711bd7c977875c6623d33f1f585870c3cc620 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-1b7
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-b48d12-2175169953 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T04:36:28+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-1b7", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T05:16:06+00:00 |
b396dee7e48b8e448126be19fabf665e6ca412dd | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-3b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269956 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:02:34+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-3b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T05:57:00+00:00 |
c657d15baf277c48d467f0625f7d33c50d4352ef |
# Dataset Card for K-MHaS
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Sample Code
<a href="https://colab.research.google.com/drive/171KhS1_LVBtpAFd_kaT8lcrZmhcz5ehY?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="base"/></a>
## Dataset Description
- **Homepage:** [K-MHaS](https://github.com/adlnlp/K-MHaS)
- **Repository:** [Korean Multi-label Hate Speech Dataset](https://github.com/adlnlp/K-MHaS)
- **Paper:** [K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online News Comment](https://arxiv.org/abs/2208.10684)
- **Point of Contact:** [Caren Han]([email protected])
- **Sample code:** [Colab](https://colab.research.google.com/drive/171KhS1_LVBtpAFd_kaT8lcrZmhcz5ehY?usp=sharing)
### Dataset Summary
The Korean Multi-label Hate Speech Dataset, **K-MHaS**, consists of 109,692 utterances from Korean online news comments, labelled with 8 fine-grained hate speech classes (labels: `Politics`, `Origin`, `Physical`, `Age`, `Gender`, `Religion`, `Race`, `Profanity`) or `Not Hate Speech` class. Each utterance provides from a single to four labels that can handles Korean language patterns effectively. For more details, please refer to our paper about [**K-MHaS**](https://aclanthology.org/2022.coling-1.311), published at COLING 2022.
### Supported Tasks and Leaderboards
Hate Speech Detection
* `binary classification` (labels: `Hate Speech`, `Not Hate Speech`)
* `multi-label classification`: (labels: `Politics`, `Origin`, `Physical`, `Age`, `Gender`, `Religion`, `Race`, `Profanity`, `Not Hate Speech`)
For the multi-label classification, a `Hate Speech` class from the binary classification, is broken down into eight classes, associated with the hate speech category. In order to reflect the social and historical context, we select the eight hate speech classes. For example, the `Politics` class is chosen, due to a significant influence on the style of Korean hate speech.
### Languages
Korean
## Dataset Structure
### Data Instances
The dataset is provided with train/validation/test set in the txt format. Each instance is a news comment with a corresponding one or more hate speech classes (labels: `Politics`, `Origin`, `Physical`, `Age`, `Gender`, `Religion`, `Race`, `Profanity`) or `Not Hate Speech` class. The label numbers matching in both English and Korean is in the data fields section.
```python
{'text':'수꼴틀딱시키들이 다 디져야 나라가 똑바로 될것같다..답이 없는 종자들ㅠ'
'label': [2, 3, 4]
}
```
### Data Fields
* `text`: utterance from Korean online news comment.
* `label`: the label numbers matching with 8 fine-grained hate speech classes and `not hate speech` class are follows.
* `0`: `Origin`(`출신차별`) hate speech based on place of origin or identity;
* `1`: `Physical`(`외모차별`) hate speech based on physical appearance (e.g. body, face) or disability;
* `2`: `Politics`(`정치성향차별`) hate speech based on political stance;
* `3`: `Profanity`(`혐오욕설`) hate speech in the form of swearing, cursing, cussing, obscene words, or expletives; or an unspecified hate speech category;
* `4`: `Age`(`연령차별`) hate speech based on age;
* `5`: `Gender`(`성차별`) hate speech based on gender or sexual orientation (e.g. woman, homosexual);
* `6`: `Race`(`인종차별`) hate speech based on ethnicity;
* `7`: `Religion`(`종교차별`) hate speech based on religion;
* `8`: `Not Hate Speech`(`해당사항없음`).
### Data Splits
In our repository, we provide splitted datasets that have 78,977(train) / 8,776 (validation) / 21,939 (test) samples, preserving the class proportion.
## Dataset Creation
### Curation Rationale
We propose K-MHaS, a large size Korean multi-label hate speech detection dataset that represents Korean language patterns effectively. Most datasets in hate speech research are annotated using a single label classification of particular aspects, even though the subjectivity of hate speech cannot be explained with a mutually exclusive annotation scheme. We propose a multi-label hate speech annotation scheme that allows overlapping labels associated with the subjectivity and the intersectionality of hate speech.
### Source Data
#### Initial Data Collection and Normalization
Our dataset is based on the Korean online news comments available on Kaggle and Github. The unlabeled raw data was collected between January 2018 and June 2020. Please see the details in our paper [K-MHaS](https://aclanthology.org/2022.coling-1.311) published at COLING2020.
#### Who are the source language producers?
The language producers are users who left the comments on the Korean online news platform between 2018 and 2020.
### Annotations
#### Annotation process
We begin with the common categories of hate speech found in literature and match the keywords for each category. After the preliminary round, we investigate the results to merge or remove labels in order to provide the most representative subtype labels of hate speech contextual to the cultural background. Our annotation instructions explain a twolayered annotation to (a) distinguish hate and not hate speech, and (b) the categories of hate speech. Annotators are requested to consider given keywords or alternatives of each category within social, cultural, and historical circumstances. For more details, please refer to the paper [K-MHaS](https://aclanthology.org/2022.coling-1.311).
#### Who are the annotators?
Five native speakers were recruited for manual annotation in both the preliminary and main rounds.
### Personal and Sensitive Information
This datasets contains examples of hateful language, however, has no personal information.
## Considerations for Using the Data
### Social Impact of Dataset
We propose K-MHaS, a new large-sized dataset for Korean hate speech detection with a multi-label annotation scheme. We provided extensive baseline experiment results, presenting the usability of a dataset to detect Korean language patterns in hate speech.
### Discussion of Biases
All annotators were recruited from a crowdsourcing platform. They were informed about hate speech before handling the data. Our instructions allowed them to feel free to leave if they were uncomfortable with the content. With respect to the potential risks, we note that the subjectivity of human annotation would impact on the quality of the dataset.
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
This dataset is curated by Taejun Lim, Heejun Lee and Bogeun Jo.
### Licensing Information
Creative Commons Attribution-ShareAlike 4.0 International (cc-by-sa-4.0).
### Citation Information
```
@inproceedings{lee-etal-2022-k,
title = "K-{MH}a{S}: A Multi-label Hate Speech Detection Dataset in {K}orean Online News Comment",
author = "Lee, Jean and
Lim, Taejun and
Lee, Heejun and
Jo, Bogeun and
Kim, Yangsok and
Yoon, Heegeun and
Han, Soyeon Caren",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.311",
pages = "3530--3538",
abstract = "Online hate speech detection has become an important issue due to the growth of online content, but resources in languages other than English are extremely limited. We introduce K-MHaS, a new multi-label dataset for hate speech detection that effectively handles Korean language patterns. The dataset consists of 109k utterances from news comments and provides a multi-label classification using 1 to 4 labels, and handles subjectivity and intersectionality. We evaluate strong baselines on K-MHaS. KR-BERT with a sub-character tokenizer outperforms others, recognizing decomposed characters in each hate speech class.",
}
```
### Contributions
The contributors of the work are:
- [Jean Lee](https://jeanlee-ai.github.io/) (The University of Sydney)
- [Taejun Lim](https://github.com/taezun) (The University of Sydney)
- [Heejun Lee](https://bigwaveai.com/) (BigWave AI)
- [Bogeun Jo](https://bigwaveai.com/) (BigWave AI)
- Yangsok Kim (Keimyung University)
- Heegeun Yoon (National Information Society Agency)
- [Soyeon Caren Han](https://drcarenhan.github.io/) (The University of Western Australia and The University of Sydney)
| jeanlee/kmhas_korean_hate_speech | [
"task_categories:text-classification",
"task_ids:multi-label-classification",
"task_ids:hate-speech-detection",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ko",
"license:cc-by-sa-4.0",
"K-MHaS",
"Korean NLP",
"Hate Speech Detection",
"Dataset",
"Coling2022",
"arxiv:2208.10684",
"region:us"
] | 2022-11-21T05:03:58+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["ko"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["multi-label-classification", "hate-speech-detection"], "paperswithcode_id": "korean-multi-label-hate-speech-dataset", "pretty_name": "K-MHaS", "tags": ["K-MHaS", "Korean NLP", "Hate Speech Detection", "Dataset", "Coling2022"], "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "label", "sequence": {"class_label": {"names": {"0": "origin", "1": "physical", "2": "politics", "3": "profanity", "4": "age", "5": "gender", "6": "race", "7": "religion", "8": "not_hate_speech"}}}}], "splits": [{"name": "train", "num_bytes": 6845463, "num_examples": 78977}, {"name": "validation", "num_bytes": 748899, "num_examples": 8776}, {"name": "test", "num_bytes": 1902352, "num_examples": 21939}], "download_size": 9496714, "dataset_size": 109692}} | 2022-11-28T16:26:56+00:00 |
e2764ebad2f0895686750be9bb6a1d32512da285 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-7b1
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269957 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:08:33+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-7b1", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T07:46:38+00:00 |
99c8e6aa83a7894662f20d54944f494f8d6ceaec | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-1b7
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269958 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:08:33+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-1b7", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T05:48:24+00:00 |
2ccc476e05d671b79bd1e165b7df9227d6424577 |
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### 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
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
| DTU54DL/common-voice-test3k | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | 2022-11-21T05:09:36+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["token-classification-other-acronym-identification"], "paperswithcode_id": "acronym-identification", "pretty_name": "Acronym Identification Dataset", "train-eval-index": [{"col_mapping": {"labels": "tags", "tokens": "tokens"}, "config": "default", "splits": {"eval_split": "test"}, "task": "token-classification", "task_id": "entity_extraction"}]} | 2022-11-21T05:14:11+00:00 |
fbe6fd6d1dbc51d943c2ee6f81494697e6676399 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-1b1
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269959 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:14:05+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-1b1", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T05:38:51+00:00 |
02e417b42b37767924bec8bfb1ead5e2fc431e15 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-560m
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-395337-2175269960 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:14:39+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "bigscience/bloom-560m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T05:39:13+00:00 |
ca2f705536a3b60346bc2504657ceb944d5731a3 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-66b
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469961 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:15:27+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-66b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-22T06:28:46+00:00 |
b93b4778189797b5b0df55bf722f61ecab05bd29 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469962 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:23:15+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-30b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T16:33:23+00:00 |
50a0af95c64759498e32f301b74c994d61229ba4 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469963 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:36:27+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-13b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T10:17:39+00:00 |
fd97c8db83aaa212343d4e641cc4609611c35123 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469964 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:36:30+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-6.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T08:41:48+00:00 |
2249d362ae1ddee0d79dfd142e0b836ef18f80d6 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-350m
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469965 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:41:21+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-350m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T06:02:48+00:00 |
6954fce5b80d439d171b0d3c07c9a259e237b602 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-1.3b
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469967 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:45:21+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-1.3b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T06:30:14+00:00 |
dab7570afff31fa06b62eb215bc313281d167346 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-2.7b
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469966 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:45:21+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-2.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T06:52:57+00:00 |
d91aa73ca834a4fa513c500681c7daa9f5cae6bb | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-125m
* Dataset: futin/feed
* Config: top_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_vi-71f14a-2175469968 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:55:48+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-125m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T06:06:13+00:00 |
201cc27e72b70ec2239aa10ba88938e13a30c852 | ArtifactAI/arxiv_abstracts_specter_faiss_flat_index | [
"region:us"
] | 2022-11-21T05:55:50+00:00 | {"license": "apache-2.0"} | 2022-11-21T06:17:43+00:00 |
|
62c464aacf3b578cb9f8e7e270f352c8ec2d4e4e |
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### 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
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
| DTU54DL/common-train-3k | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | 2022-11-21T05:58:02+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["token-classification-other-acronym-identification"], "paperswithcode_id": "acronym-identification", "pretty_name": "Acronym Identification Dataset", "train-eval-index": [{"col_mapping": {"labels": "tags", "tokens": "tokens"}, "config": "default", "splits": {"eval_split": "test"}, "task": "token-classification", "task_id": "entity_extraction"}]} | 2022-11-21T06:16:54+00:00 |
db4bcaceb3594e934caee27504a707ebdf296dcf | gayom/styletransfer-dataset | [
"region:us"
] | 2022-11-21T05:58:09+00:00 | {} | 2022-11-22T04:03:16+00:00 |
|
94b45268f8e909751b05fd0d72b0fea941556d02 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-66b
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569969 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T05:58:43+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-66b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-22T12:19:01+00:00 |
04e9e802e46376553ce2831908cb596ce07dc0e6 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569970 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T06:03:07+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-30b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T19:57:40+00:00 |
5aea7c9c198cbf6c17354ddfadaf8d425b502599 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569971 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T06:03:29+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-13b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T11:48:55+00:00 |
4eb87d26e980987d559b87160856baa11109f0dd | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569972 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T06:09:45+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-6.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T09:24:28+00:00 |
d951046ca4dc26d79cb0795a2e77b031d51406ab | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-350m
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569973 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T06:13:14+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-350m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T06:24:47+00:00 |
faf2a3209e88598962a44ec90d231f1c80ccb940 |
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### 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
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
| DTU54DL/common3k-train | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | 2022-11-21T06:18:09+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["token-classification-other-acronym-identification"], "paperswithcode_id": "acronym-identification", "pretty_name": "Acronym Identification Dataset", "train-eval-index": [{"col_mapping": {"labels": "tags", "tokens": "tokens"}, "config": "default", "splits": {"eval_split": "test"}, "task": "token-classification", "task_id": "entity_extraction"}]} | 2022-11-21T06:29:04+00:00 |
dd11ad0beab677041f45bec373c053d6cd9107ea | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-2.7b
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569974 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T06:32:43+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-2.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T07:33:13+00:00 |
726435adf1bc22e101cf621126d45450d7802ed7 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-1.3b
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569975 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T06:37:55+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-1.3b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T07:12:40+00:00 |
205e2c3097d442712bc29e8e685e24ead788fff2 | sakun/facedepth | [
"license:afl-3.0",
"region:us"
] | 2022-11-21T06:46:48+00:00 | {"license": "afl-3.0"} | 2022-11-21T06:46:48+00:00 |
|
5d35434e76378b4733abb84952bcdef1db149a5f | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-125m
* Dataset: futin/feed
* Config: top_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569976 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:00:49+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-125m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "top_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T07:06:54+00:00 |
ff8caca1c9d644e6068212df575de08ab5ae4535 | # Dataset Card for "msp_train_hubert_large"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | dlproject/msp_train_hubert_large | [
"region:us"
] | 2022-11-21T07:08:21+00:00 | {"dataset_info": {"features": [{"name": "input_values", "sequence": {"sequence": {"sequence": "float32"}}}, {"name": "attention_mask", "sequence": {"sequence": "int32"}}, {"name": "labels", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 10873164220, "num_examples": 29939}], "download_size": 9851610543, "dataset_size": 10873164220}} | 2022-11-21T07:13:29+00:00 |
4ab533d071876e1c72b216346b067ef847213336 | # Dataset Card for "msp_val_hubert_large"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | dlproject/msp_val_hubert_large | [
"region:us"
] | 2022-11-21T07:13:29+00:00 | {"dataset_info": {"features": [{"name": "input_values", "sequence": {"sequence": {"sequence": "float32"}}}, {"name": "attention_mask", "sequence": {"sequence": "int32"}}, {"name": "labels", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 1895911184, "num_examples": 5213}], "download_size": 1773617134, "dataset_size": 1895911184}} | 2022-11-21T07:14:35+00:00 |
2585c70adc22318cb43e027e6010adb3bf7e2d57 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-66b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669977 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:15:24+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-66b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-22T02:38:23+00:00 |
c8044476b3337c8c35a9f1c9343c843125a1577c | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669978 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:20:53+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-30b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T15:42:35+00:00 |
e5b2a640e1c97c48eaa06653a5e2db825ea346b8 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669979 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:28:15+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-13b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T11:06:18+00:00 |
fa1c5303e1a07cb34b30343c69321b0d2429da5d | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669980 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:40:54+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-6.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T09:56:56+00:00 |
a094e286b1457c23adba95cbfc1f4d1a6b50ef4a | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-90bfb636-8600-4a27-9171-c297c5e7f496-3331 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:46:57+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T07:47:36+00:00 |
75adebf2c84ae40483403b596606a37ac2a32cef | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-350m
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669981 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T07:54:36+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-350m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T08:09:55+00:00 |
b105b430df1564b8bdc5ac6177d9c6a3b5975cc7 | # Dataset Card for "hewiki-20220901-articles-dataset" | Norod78/hewiki-20220901-articles-dataset | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:100M<n<1B",
"source_datasets:extended|wikipedia",
"language:he",
"he-wiki",
"region:us"
] | 2022-11-21T08:10:15+00:00 | {"annotations_creators": ["other"], "language_creators": ["other"], "language": ["he"], "multilinguality": ["monolingual"], "size_categories": ["100M<n<1B"], "source_datasets": ["extended|wikipedia"], "task_categories": ["text-generation", "fill-mask"], "task_ids": ["language-modeling", "masked-language-modeling"], "pretty_name": "hewiki Corpus from hewiki-20220901-pages-articles-multistream.xml.bz2", "dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1458031124, "num_examples": 4325836}], "download_size": 745537027, "dataset_size": 1458031124}, "tags": ["he-wiki"]} | 2022-11-22T10:57:40+00:00 |
35871bc78c1b18b0daddb4755de6958b74e5e7e3 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-2.7b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669982 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T08:18:25+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-2.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T09:11:01+00:00 |
947acb9c2813ba049626c04c763d3cdd33d323aa | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-1.3b
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669983 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T08:22:39+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-1.3b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T08:57:24+00:00 |
6db038e924e20d99a5e54609f8a6ea9102acd71c | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-125m
* Dataset: futin/feed
* Config: sen_vi
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_vi-894567-2175669984 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T08:32:13+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-125m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_vi", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T08:40:18+00:00 |
109e53ccded0e0d4f99a9368e979fee941e0ba56 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769986 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T08:48:29+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-30b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T17:11:57+00:00 |
e18322fdf0714ab7a56a1425d11b6abecfcb6967 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-66b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769985 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T08:48:30+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-66b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-22T03:31:20+00:00 |
ee40c02a4c1a8ba4628c02c42666ff9c257040ed | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769987 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T09:05:34+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-13b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T12:43:31+00:00 |
e1c59067e2deae56f90c00caed6af3da7bae44e8 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769988 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T09:19:19+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-6.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T11:32:30+00:00 |
dfa01f6bbb4a9aebec5d0ba15d2c3966bb7d596d | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-350m
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769989 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T09:32:41+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-350m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T09:42:14+00:00 |
caf2b0bc2acce6c4d715b9eb3b7f3d9dc74ddd32 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-2.7b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769990 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T09:50:16+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-2.7b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T10:30:32+00:00 |
3f192f10d4c478b765cf9ce88bdac32f27b39292 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-1.3b
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769991 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:04:58+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-1.3b", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T10:32:30+00:00 |
7fdd4bcbede3df8b0c9c66415587c49c6b4d4aaf | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-977d15c2-b4b7-4875-aee0-490ae596d0f4-3432 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:15:43+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T10:16:21+00:00 |
ce04a3c58735371bebf755f27f3677572f47eed4 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-6a3804e2-ad4c-48af-8aa6-4620beed26ac-3533 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:18:27+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T10:19:04+00:00 |
a54c63330c72c77324fccfb9b9fe9a86bcba95cf | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-125m
* Dataset: futin/feed
* Config: sen_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 [@futin](https://huggingface.co/futin) for evaluating this model. | autoevaluate/autoeval-eval-futin__feed-sen_en-2f01d7-2175769992 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:25:57+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["futin/feed"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-125m", "metrics": [], "dataset_name": "futin/feed", "dataset_config": "sen_en", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T10:30:40+00:00 |
9926d1b2c02e5c779f26d996d6bea72e11a1ea1c | dnwalkup/db_regularization_images | [
"license:other",
"region:us"
] | 2022-11-21T10:29:16+00:00 | {"license": "other"} | 2022-11-23T10:58:35+00:00 |
|
b7395a5d6dc7c2de75b8ba5b657ec80ea1b63922 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-50a56796-db2d-4349-bf75-388efb52b967-3634 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:33:29+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T10:34:05+00:00 |
29e2b696c2d114e1f818d7565460513d1ddfd783 | # Dataset Card for "test_push_default"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | polinaeterna/test_push_default | [
"region:us"
] | 2022-11-21T10:40:26+00:00 | {"dataset_info": [{"features": [{"name": "x", "dtype": "int64"}, {"name": "y", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 74, "num_examples": 5}, {"name": "test", "num_bytes": 88, "num_examples": 6}], "download_size": 854, "dataset_size": 162}, {"config_name": "v3", "features": [{"name": "x", "dtype": "int64"}, {"name": "y", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 74, "num_examples": 5}, {"name": "test", "num_bytes": 88, "num_examples": 6}], "download_size": 0, "dataset_size": 162}]} | 2022-11-21T11:05:37+00:00 |
fd12239c2aee5a9e78a5331acded8fcc133a63c1 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-48057538-ec1b-4e18-ac2b-35070fb8202e-3735 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:44:49+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T10:45:25+00:00 |
2f9ef1050de57018488761533ba79a92eab48c12 |
# Dataset Card for MT-GenEval
## Table of Contents
- [Dataset Card for MT-GenEval](#dataset-card-for-mt-geneval)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Machine Translation](#machine-translation)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Repository:** [Github](https://github.com/amazon-science/machine-translation-gender-eval)
- **Paper:** [EMNLP 2022](https://arxiv.org/abs/2211.01355)
- **Point of Contact:** [Anna Currey](mailto:[email protected])
### Dataset Summary
The MT-GenEval benchmark evaluates gender translation accuracy on English -> {Arabic, French, German, Hindi, Italian, Portuguese, Russian, Spanish}. The dataset contains individual sentences with annotations on the gendered target words, and contrastive original-invertend translations with additional preceding context.
**Disclaimer**: *The MT-GenEval benchmark was released in the EMNLP 2022 paper [MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation](https://arxiv.org/abs/2211.01355) by Anna Currey, Maria Nadejde, Raghavendra Pappagari, Mia Mayer, Stanislas Lauly, Xing Niu, Benjamin Hsu, and Georgiana Dinu and is hosted through Github by the [Amazon Science](https://github.com/amazon-science?type=source) organization. The dataset is licensed under a [Creative Commons Attribution-ShareAlike 3.0 Unported License](https://creativecommons.org/licenses/by-sa/3.0/).*
### Supported Tasks and Leaderboards
#### Machine Translation
Refer to the [original paper](https://arxiv.org/abs/2211.01355) for additional details on gender accuracy evaluation with MT-GenEval.
### Languages
The dataset contains source English sentences extracted from Wikipedia translated into the following languages: Arabic (`ar`), French (`fr`), German (`de`), Hindi (`hi`), Italian (`it`), Portuguese (`pt`), Russian (`ru`), and Spanish (`es`).
## Dataset Structure
### Data Instances
The dataset contains two configuration types, `sentences` and `context`, mirroring the original repository structure, with source and target language specified in the configuration name (e.g. `sentences_en_ar`, `context_en_it`) The `sentences` configurations contains masculine and feminine versions of individual sentences with gendered word annotations. Here is an example entry of the `sentences_en_it` split (all `sentences_en_XX` splits have the same structure):
```json
{
{
"orig_id": 0,
"source_feminine": "Pagratidis quickly recanted her confession, claiming she was psychologically pressured and beaten, and until the moment of her execution, she remained firm in her innocence.",
"reference_feminine": "Pagratidis subito ritrattò la sua confessione, affermando che era aveva subito pressioni psicologiche e era stata picchiata, e fino al momento della sua esecuzione, rimase ferma sulla sua innocenza.",
"source_masculine": "Pagratidis quickly recanted his confession, claiming he was psychologically pressured and beaten, and until the moment of his execution, he remained firm in his innocence.",
"reference_masculine": "Pagratidis subito ritrattò la sua confessione, affermando che era aveva subito pressioni psicologiche e era stato picchiato, e fino al momento della sua esecuzione, rimase fermo sulla sua innocenza.",
"source_feminine_annotated": "Pagratidis quickly recanted <F>her</F> confession, claiming <F>she</F> was psychologically pressured and beaten, and until the moment of <F>her</F> execution, <F>she</F> remained firm in <F>her</F> innocence.",
"reference_feminine_annotated": "Pagratidis subito ritrattò la sua confessione, affermando che era aveva subito pressioni psicologiche e era <F>stata picchiata</F>, e fino al momento della sua esecuzione, rimase <F>ferma</F> sulla sua innocenza.",
"source_masculine_annotated": "Pagratidis quickly recanted <M>his</M> confession, claiming <M>he</M> was psychologically pressured and beaten, and until the moment of <M>his</M> execution, <M>he</M> remained firm in <M>his</M> innocence.",
"reference_masculine_annotated": "Pagratidis subito ritrattò la sua confessione, affermando che era aveva subito pressioni psicologiche e era <M>stato picchiato</M>, e fino al momento della sua esecuzione, rimase <M>fermo</M> sulla sua innocenza.",
"source_feminine_keywords": "her;she;her;she;her",
"reference_feminine_keywords": "stata picchiata;ferma",
"source_masculine_keywords": "his;he;his;he;his",
"reference_masculine_keywords": "stato picchiato;fermo",
}
}
```
The `context` configuration contains instead different English sources related to stereotypical professional roles with additional preceding context and contrastive original-inverted translations. Here is an example entry of the `context_en_it` split (all `context_en_XX` splits have the same structure):
```json
{
"orig_id": 0,
"context": "Pierpont told of entering and holding up the bank and then fleeing to Fort Wayne, where the loot was divided between him and three others.",
"source": "However, Pierpont stated that Skeer was the planner of the robbery.",
"reference_original": "Comunque, Pierpont disse che Skeer era il pianificatore della rapina.",
"reference_flipped": "Comunque, Pierpont disse che Skeer era la pianificatrice della rapina."
}
```
### Data Splits
All `sentences_en_XX` configurations have 1200 examples in the `train` split and 300 in the `test` split. For the `context_en_XX` configurations, the number of example depends on the language pair:
| Configuration | # Train | # Test |
| :-----------: | :--------: | :-----: |
| `context_en_ar` | 792 | 1100 |
| `context_en_fr` | 477 | 1099 |
| `context_en_de` | 598 | 1100 |
| `context_en_hi` | 397 | 1098 |
| `context_en_it` | 465 | 1904 |
| `context_en_pt` | 574 | 1089 |
| `context_en_ru` | 583 | 1100 |
| `context_en_es` | 534 | 1096 |
### Dataset Creation
From the original paper:
>In developing MT-GenEval, our goal was to create a realistic, gender-balanced dataset that naturally incorporates a diverse range of gender phenomena. To this end, we extracted English source sentences from Wikipedia as the basis for our dataset. We automatically pre-selected relevant sentences using EN gender-referring words based on the list provided by [Zhao et al. (2018)](https://doi.org/10.18653/v1/N18-2003).
Please refer to the original article [MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation](https://arxiv.org/abs/2211.01355) for additional information on dataset creation.
## Additional Information
### Dataset Curators
The original authors of MT-GenEval are the curators of the original dataset. For problems or updates on this 🤗 Datasets version, please contact [[email protected]](mailto:[email protected]).
### Licensing Information
The dataset is licensed under the [Creative Commons Attribution-ShareAlike 3.0 International License](https://creativecommons.org/licenses/by-sa/3.0/).
### Citation Information
Please cite the authors if you use these corpora in your work.
```bibtex
@inproceedings{currey-etal-2022-mtgeneval,
title = "{MT-GenEval}: {A} Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation",
author = "Currey, Anna and
Nadejde, Maria and
Pappagari, Raghavendra and
Mayer, Mia and
Lauly, Stanislas, and
Niu, Xing and
Hsu, Benjamin and
Dinu, Georgiana",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/2211.01355",
}
``` | gsarti/mt_geneval | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:it",
"language:fr",
"language:ar",
"language:de",
"language:hi",
"language:pt",
"language:ru",
"language:es",
"license:cc-by-sa-3.0",
"gender",
"constrained mt",
"arxiv:2211.01355",
"region:us"
] | 2022-11-21T10:50:15+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en", "it", "fr", "ar", "de", "hi", "pt", "ru", "es"], "license": ["cc-by-sa-3.0"], "multilinguality": ["translation"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["translation"], "task_ids": [], "pretty_name": "mt_geneval", "tags": ["gender", "constrained mt"]} | 2022-11-21T14:52:09+00:00 |
b5816ba2e4436e9be858547afaba6041de6d5f68 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-d545d554-fb32-43d5-a9dd-4a47f0efba15-3836 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:51:40+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T10:52:16+00:00 |
28ea421edc80c424700633d646008ca264ce5f72 | nlhappy/CHIP-TC | [
"license:mit",
"region:us"
] | 2022-11-21T10:59:59+00:00 | {"license": "mit"} | 2022-11-21T11:00:42+00:00 |
|
dd70eea6d32e3a131961fedb5fd9856021f50e15 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-408e9b4e-b238-40e9-a460-4dacc071ae0d-3937 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:08:03+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T11:08:40+00:00 |
db839962ac0799010de37a6bda56621c3df883f1 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-be841b2c-fd99-4cdf-be00-1a826c9f1b02-4038 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:12:23+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T11:12:59+00:00 |
c2cc6f084e36682eda391875e8af350aad0e86a5 | # Dataset Card for "test_push_new"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | polinaeterna/test_push_new | [
"region:us"
] | 2022-11-21T11:15:45+00:00 | {"dataset_info": [{"config_name": "v3", "features": [{"name": "x", "dtype": "int64"}, {"name": "y", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 74, "num_examples": 5}, {"name": "test", "num_bytes": 88, "num_examples": 6}], "download_size": 1704, "dataset_size": 162}]} | 2022-11-21T11:16:30+00:00 |
b50b21cc833c01212c55c7d7b433a5a826c6f904 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-a3656eb0-b7ed-410f-ab65-0222b8e06770-4139 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:21:05+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T11:21:43+00:00 |
8df313e77edb0bc54fab01a46f001f00ac6f9603 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-e8ce9c11-cb63-47ba-8b24-d3a9a8e15a88-4240 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:25:31+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T11:26:20+00:00 |
66745b3dce8aa8db16e3319df0519d6e8c872d1c | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-0919d128-ac07-4f9a-b929-706957da9f2e-4341 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:31:02+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T11:31:50+00:00 |
a1b620a256a4f15fa17800e8e762a6dd35e7d41e | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-8abfadbc-69e6-47d0-afdc-f5859c5e0d16-4442 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:37:25+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T11:38:08+00:00 |
2d9a23d68941979f794480720b50c2cb0c81fd5c | # Dataset Card for "birddb_small2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | kojima-r/birddb_small2 | [
"region:us"
] | 2022-11-21T12:18:24+00:00 | {"dataset_info": {"features": [{"name": "audio", "dtype": "audio"}], "splits": [{"name": "train", "num_bytes": 1011384430.775, "num_examples": 77501}], "download_size": 2139041561, "dataset_size": 1011384430.775}} | 2022-11-21T12:22:41+00:00 |
c4195463f4bcf741934ab7e2d1169a5a5ac78402 | GR4DF/astheber | [
"license:afl-3.0",
"region:us"
] | 2022-11-21T12:40:57+00:00 | {"license": "afl-3.0"} | 2022-11-21T12:41:12+00:00 |
|
af4407172632a9ed0f90fc7ff59c7a83cb614bd3 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-688c59a8-44a3-4de2-8b30-d3e76d3addf5-4543 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T12:41:17+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T12:42:01+00:00 |
e7e31982c6139f0f0872ce16204b560e6bd3c3bc | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-5a4fda18-6304-4b90-86c0-99202bfbe1e9-4644 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T12:45:40+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T12:46:22+00:00 |
23202693ec578a5d9c1d82bbf7409668f4704375 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-4144bd7b-94bf-4e9e-87a5-f722d28cd7cd-4745 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T12:58:49+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T12:59:31+00:00 |
3c644988582d3df5115558885f42dddf91aa6cc3 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-636a44ed-fa98-4717-b181-b742a86b03be-4846 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:01:47+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T13:02:29+00:00 |
238462195650d028dc3c1cd4c0ce345f68fd71b5 | Just a collection of the TI's Ive made. Idk how to really use huggingface so im just gona put the descriptions here
1. araken - @Ara_Kieda. have not really tested it but from what I have tested, it works alright.
2. izuna - character TI of Kuda Izuna from Blue Archive. Needs at least three token to change outfit. (((token)))
3. jizel - @jizell_7. was trained on very few datasets so its very biased to brown hair.
4. mikapikazo - @MikaPikaZo. Really looks good on prompts with "muticolored".
5. matcha - @matchach. this was my first TI and its overtrained. Really cool style tho.
6. nanmokaken - @nanmokaken. kemonomimi lolis
7. onene - @OneneChan. havent really tested this yet but it does resemble their works.
8. orieh - @orie_h. really unique watercolor style.
9. rurudo - @rurudo_. sometimes it works, sometimes it doesnt.
10. yukoring - @_yukoring. watercolor style but hair does sometimes get weird.
11. teraru - @TeraAru6262. I tried training this for the hair styles but it failed.
12. iftuoma - @iftuoma. Failed TI. was just too lazy to sort out datasets and couldnt be bothered doing it now. | Katekii/TI | [
"region:us"
] | 2022-11-21T13:04:07+00:00 | {} | 2022-11-22T09:39:33+00:00 |
94b751e72f33e95797ff8b5b786e551a0acb038b | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-11ed4317-15c4-4e98-9e37-8cdfe6d38dfb-4947 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:05:17+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T13:06:00+00:00 |
4217838c01c04186ef75ebb624a2adf02d460b23 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- mit
multilinguality:
- monolingual
paperswithcode_id: acronym-identification
pretty_name: Acronym Identification Dataset
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- token-classification-other-acronym-identification
train-eval-index:
- col_mapping:
labels: tags
tokens: tokens
config: default
splits:
eval_split: test
task: token-classification
task_id: entity_extraction---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### 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
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
| DTU54DL/commo-test1k-whisper-proc | [
"region:us"
] | 2022-11-21T13:08:42+00:00 | {} | 2022-11-21T13:30:24+00:00 |
b49866491c9f9bf9baa1c6c61ac7a9292b2efbc9 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-b2b60f7a-3ccf-4daf-af67-2833dd712c28-5048 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:08:52+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T13:09:34+00:00 |
5895f5d10bbdba5b66f6baa23360a7b3dcd9f902 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-2302ec60-cb56-482a-8d70-ce549b14fd54-5149 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:14:01+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T13:14:43+00:00 |
dbbb28c914a180071f9fe5e95b4c409459bae379 | # 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: autoevaluate/multi-class-classification
* Dataset: emotion
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-318525f4-cdf7-4888-965c-d4d9dfeeca48-5250 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:19:56+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["emotion"], "eval_info": {"task": "multi_class_classification", "model": "autoevaluate/multi-class-classification", "metrics": ["matthews_correlation"], "dataset_name": "emotion", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "text", "target": "label"}}} | 2022-11-21T13:20:39+00:00 |
e74d373ce6454eedc53107b793b08ec0d6d7b8a3 | # 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: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-5c51f1de-f5e2-46a7-861f-b1b7c80db774-5351 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:25:52+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "binary_classification", "model": "autoevaluate/binary-classification", "metrics": ["matthews_correlation"], "dataset_name": "glue", "dataset_config": "sst2", "dataset_split": "validation", "col_mapping": {"text": "sentence", "target": "label"}}} | 2022-11-21T13:26:28+00:00 |
da173b9242eb26134365c4b17e69d4a2ded03b8f | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: autoevaluate/zero-shot-classification
* Dataset: autoevaluate/zero-shot-classification-sample
* Config: autoevaluate--zero-shot-classification-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-a02353d8-c94a-4476-bd14-15028ee3f918-5452 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:32:44+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/zero-shot-classification-sample"], "eval_info": {"task": "text_zero_shot_classification", "model": "autoevaluate/zero-shot-classification", "metrics": [], "dataset_name": "autoevaluate/zero-shot-classification-sample", "dataset_config": "autoevaluate--zero-shot-classification-sample", "dataset_split": "test", "col_mapping": {"text": "text", "classes": "classes", "target": "target"}}} | 2022-11-21T13:33:16+00:00 |
d14d164ed864c6702a44a2384c2b04f0737e8df1 | # 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: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-31466167-6d47-4d63-9ebd-59fe66b62d96-5553 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:38:58+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "natural_language_inference", "model": "autoevaluate/natural-language-inference", "metrics": [], "dataset_name": "glue", "dataset_config": "mrpc", "dataset_split": "validation", "col_mapping": {"text1": "sentence1", "text2": "sentence2", "target": "label"}}} | 2022-11-21T13:39:35+00:00 |
635f1f6b24ac85800a7c0b94c644fd888a5c8e4e | # Dataset Card for GoEmotions
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://github.com/google-research/google-research/tree/master/goemotions
- **Repository:** https://github.com/google-research/google-research/tree/master/goemotions
- **Paper:** https://arxiv.org/abs/2005.00547
- **Leaderboard:**
- **Point of Contact:** [Dora Demszky](https://nlp.stanford.edu/~ddemszky/index.html)
### Dataset Summary
The GoEmotions dataset contains 58k carefully curated Reddit comments labeled for 27 emotion categories or Neutral.
The raw data is included as well as the smaller, simplified version of the dataset with predefined train/val/test
splits.
### Supported Tasks and Leaderboards
This dataset is intended for multi-class, multi-label emotion classification.
### Languages
The data is in English and Brazilian Portuguese (translated by Google Translator).
## Dataset Structure
### Data Instances
Each instance is a reddit comment with a corresponding ID and one or more emotion annotations (or neutral).
### Data Fields
The simplified configuration includes:
- `text`: the reddit comment
- `texto`: the reddit comment in portuguese
- `labels`: the emotion annotations
- `comment_id`: unique identifier of the comment (can be used to look up the entry in the raw dataset)
In addition to the above, the raw data includes:
* `author`: The Reddit username of the comment's author.
* `subreddit`: The subreddit that the comment belongs to.
* `link_id`: The link id of the comment.
* `parent_id`: The parent id of the comment.
* `created_utc`: The timestamp of the comment.
* `rater_id`: The unique id of the annotator.
* `example_very_unclear`: Whether the annotator marked the example as being very unclear or difficult to label (in this
case they did not choose any emotion labels).
In the raw data, labels are listed as their own columns with binary 0/1 entries rather than a list of ids as in the
simplified data.
### Data Splits
The simplified data includes a set of train/val/test splits with 43,410, 5426, and 5427 examples respectively.
## Dataset Creation
### Curation Rationale
From the paper abstract:
> Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to
detecting harmful online behavior. Advancement in this area can be improved using large-scale datasets with a
fine-grained typology, adaptable to multiple downstream tasks.
### Source Data
#### Initial Data Collection and Normalization
Data was collected from Reddit comments via a variety of automated methods discussed in 3.1 of the paper.
#### Who are the source language producers?
English-speaking Reddit users.
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
Annotations were produced by 3 English-speaking crowdworkers in India.
### Personal and Sensitive Information
This dataset includes the original usernames of the Reddit users who posted each comment. Although Reddit usernames
are typically disasociated from personal real-world identities, this is not always the case. It may therefore be
possible to discover the identities of the individuals who created this content in some cases.
## Considerations for Using the Data
### Social Impact of Dataset
Emotion detection is a worthwhile problem which can potentially lead to improvements such as better human/computer
interaction. However, emotion detection algorithms (particularly in computer vision) have been abused in some cases
to make erroneous inferences in human monitoring and assessment applications such as hiring decisions, insurance
pricing, and student attentiveness (see
[this article](https://www.unite.ai/ai-now-institute-warns-about-misuse-of-emotion-detection-software-and-other-ethical-issues/)).
### Discussion of Biases
From the authors' github page:
> Potential biases in the data include: Inherent biases in Reddit and user base biases, the offensive/vulgar word lists used for data filtering, inherent or unconscious bias in assessment of offensive identity labels, annotators were all native English speakers from India. All these likely affect labelling, precision, and recall for a trained model. Anyone using this dataset should be aware of these limitations of the dataset.
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
Researchers at Amazon Alexa, Google Research, and Stanford. See the [author list](https://arxiv.org/abs/2005.00547).
### Licensing Information
The GitHub repository which houses this dataset has an
[Apache License 2.0](https://github.com/google-research/google-research/blob/master/LICENSE).
### Citation Information
@inproceedings{demszky2020goemotions,
author = {Demszky, Dorottya and Movshovitz-Attias, Dana and Ko, Jeongwoo and Cowen, Alan and Nemade, Gaurav and Ravi, Sujith},
booktitle = {58th Annual Meeting of the Association for Computational Linguistics (ACL)},
title = {{GoEmotions: A Dataset of Fine-Grained Emotions}},
year = {2020}
}
### Contributions
Thanks to [@joeddav](https://github.com/joeddav) for adding this dataset.
Thanks to [@antoniomenezes](https://github.com/antoniomenezes) for extending this dataset. | antoniomenezes/go_emotions_ptbr | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:multi-label-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:2 languages",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"source_datasets:modified",
"language:en",
"language:pt",
"license:apache-2.0",
"emotion",
"arxiv:2005.00547",
"region:us"
] | 2022-11-21T13:38:59+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en", "pt"], "license": ["apache-2.0"], "multilinguality": ["2 languages"], "size_categories": ["100K<n<1M", "10K<n<100K"], "source_datasets": ["modified"], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification", "multi-label-classification"], "paperswithcode_id": "goemotions", "pretty_name": "GoEmotions", "configs": ["raw", "simplified"], "tags": ["emotion"], "dataset_info": [{"config_name": "raw", "features": [{"name": "text", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "author", "dtype": "string"}, {"name": "subreddit", "dtype": "string"}, {"name": "link_id", "dtype": "string"}, {"name": "parent_id", "dtype": "string"}, {"name": "created_utc", "dtype": "float32"}, {"name": "rater_id", "dtype": "int32"}, {"name": "example_very_unclear", "dtype": "bool"}, {"name": "admiration", "dtype": "int32"}, {"name": "amusement", "dtype": "int32"}, {"name": "anger", "dtype": "int32"}, {"name": "annoyance", "dtype": "int32"}, {"name": "approval", "dtype": "int32"}, {"name": "caring", "dtype": "int32"}, {"name": "confusion", "dtype": "int32"}, {"name": "curiosity", "dtype": "int32"}, {"name": "desire", "dtype": "int32"}, {"name": "disappointment", "dtype": "int32"}, {"name": "disapproval", "dtype": "int32"}, {"name": "disgust", "dtype": "int32"}, {"name": "embarrassment", "dtype": "int32"}, {"name": "excitement", "dtype": "int32"}, {"name": "fear", "dtype": "int32"}, {"name": "gratitude", "dtype": "int32"}, {"name": "grief", "dtype": "int32"}, {"name": "joy", "dtype": "int32"}, {"name": "love", "dtype": "int32"}, {"name": "nervousness", "dtype": "int32"}, {"name": "optimism", "dtype": "int32"}, {"name": "pride", "dtype": "int32"}, {"name": "realization", "dtype": "int32"}, {"name": "relief", "dtype": "int32"}, {"name": "remorse", "dtype": "int32"}, {"name": "sadness", "dtype": "int32"}, {"name": "surprise", "dtype": "int32"}, {"name": "neutral", "dtype": "int32"}, {"name": "texto", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 55343630, "num_examples": 211225}], "download_size": 42742918, "dataset_size": 55343630}, {"config_name": "simplified", "features": [{"name": "text", "dtype": "string"}, {"name": "labels", "sequence": {"class_label": {"names": {"0": "admiration", "1": "amusement", "2": "anger", "3": "annoyance", "4": "approval", "5": "caring", "6": "confusion", "7": "curiosity", "8": "desire", "9": "disappointment", "10": "disapproval", "11": "disgust", "12": "embarrassment", "13": "excitement", "14": "fear", "15": "gratitude", "16": "grief", "17": "joy", "18": "love", "19": "nervousness", "20": "optimism", "21": "pride", "22": "realization", "23": "relief", "24": "remorse", "25": "sadness", "26": "surprise", "27": "neutral"}}}}, {"name": "id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 4224198, "num_examples": 43410}, {"name": "validation", "num_bytes": 527131, "num_examples": 5426}, {"name": "test", "num_bytes": 524455, "num_examples": 5427}], "download_size": 4394818, "dataset_size": 5275784}]} | 2022-11-21T14:27:31+00:00 |
467f37cd03184724d1eed773bd22e1ef43df859e | # 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: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-fa97c361-989b-438c-bd2b-73aa1588c214-5654 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:45:42+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "natural_language_inference", "model": "autoevaluate/natural-language-inference", "metrics": [], "dataset_name": "glue", "dataset_config": "mrpc", "dataset_split": "validation", "col_mapping": {"text1": "sentence1", "text2": "sentence2", "target": "label"}}} | 2022-11-21T13:46:15+00:00 |
6d71faac5cd426ecd355ddafd2967db90635b9ea | # 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: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-03e83e3b-2528-4e84-b075-34edd28549da-5755 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:53:36+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "natural_language_inference", "model": "autoevaluate/natural-language-inference", "metrics": [], "dataset_name": "glue", "dataset_config": "mrpc", "dataset_split": "validation", "col_mapping": {"text1": "sentence1", "text2": "sentence2", "target": "label"}}} | 2022-11-21T13:54:09+00:00 |
7b042f2d8fa83b6c30cd8077fb5ce1e0840d2600 | # 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: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-6ba515cb-e9ef-49fe-9bb8-a4281c03605e-5856 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:04:10+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "natural_language_inference", "model": "autoevaluate/natural-language-inference", "metrics": [], "dataset_name": "glue", "dataset_config": "mrpc", "dataset_split": "validation", "col_mapping": {"text1": "sentence1", "text2": "sentence2", "target": "label"}}} | 2022-11-21T14:04:47+00:00 |
4705079801edd2cacb314c86ce69c593934a1ab3 | # 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: autoevaluate/natural-language-inference
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-371fafb5-556b-4565-a7bf-530b1396895e-5957 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:10:27+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["glue"], "eval_info": {"task": "natural_language_inference", "model": "autoevaluate/natural-language-inference", "metrics": [], "dataset_name": "glue", "dataset_config": "mrpc", "dataset_split": "validation", "col_mapping": {"text1": "sentence1", "text2": "sentence2", "target": "label"}}} | 2022-11-21T14:11:01+00:00 |
418264ca3343afbed3297ae861a96d352032d339 | # 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: autoevaluate/entity-extraction
* Dataset: autoevaluate/conll2003-sample
* Config: autoevaluate--conll2003-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-e2e28e52-014f-41d6-a473-008f1f5e4d3d-6058 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:15:02+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/conll2003-sample"], "eval_info": {"task": "entity_extraction", "model": "autoevaluate/entity-extraction", "metrics": [], "dataset_name": "autoevaluate/conll2003-sample", "dataset_config": "autoevaluate--conll2003-sample", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}} | 2022-11-21T14:15:39+00:00 |
cd348cda88fc5bf04f04e1cf878a6093fadb96ee | # 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: autoevaluate/entity-extraction
* Dataset: autoevaluate/conll2003-sample
* Config: autoevaluate--conll2003-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-19f625bb-a07b-4f3a-bec2-d734d6029176-6159 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:18:39+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/conll2003-sample"], "eval_info": {"task": "entity_extraction", "model": "autoevaluate/entity-extraction", "metrics": [], "dataset_name": "autoevaluate/conll2003-sample", "dataset_config": "autoevaluate--conll2003-sample", "dataset_split": "test", "col_mapping": {"tokens": "tokens", "tags": "ner_tags"}}} | 2022-11-21T14:19:12+00:00 |
54f67708bcbadd0e7197a5a1381583eb4939bbd7 |
These word embeddings were computed using the POLAR technique to reproject 'common' word embeddings into roundabout 700 interpretable dimensions of polar opposites (i.e. good/bad).
I just used their scripts here:
https://github.com/Sandipan99/POLAR
I applied those on the wikidata5m embeddings, 5 million knowledge graph embeddings (SimplE).
https://graphvite.io/docs/latest/pretrained_model.html
As the model became too huge, I further filtered it for overlap with fasttext embedding tokens.
Not all dimensions make sense, this is a work in progress.
I intend to remove dimensions which turn out to not make sense, when using them. | KnutJaegersberg/interpretable_word_embeddings | [
"license:mit",
"region:us"
] | 2022-11-21T14:21:38+00:00 | {"license": "mit"} | 2022-11-25T12:10:11+00:00 |
1625be97f42d20fac451bac1daa4f69cb1374594 | # 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: autoevaluate/extractive-question-answering
* Dataset: autoevaluate/squad-sample
* Config: autoevaluate--squad-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-e438add5-1e56-41ec-9c26-2ad4182383b0-6260 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:27:41+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/squad-sample"], "eval_info": {"task": "extractive_question_answering", "model": "autoevaluate/extractive-question-answering", "metrics": [], "dataset_name": "autoevaluate/squad-sample", "dataset_config": "autoevaluate--squad-sample", "dataset_split": "test", "col_mapping": {"context": "context", "question": "question", "answers-text": "answers.text", "answers-answer_start": "answers.answer_start"}}} | 2022-11-21T14:28:17+00:00 |
29eb805ff0abb2bc32f0b8404f59c4c1d071b909 | # 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: autoevaluate/summarization
* Dataset: autoevaluate/xsum-sample
* Config: autoevaluate--xsum-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-b40c7dea-3c58-4f26-a941-b0221649edda-6362 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:34:51+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/xsum-sample"], "eval_info": {"task": "summarization", "model": "autoevaluate/summarization", "metrics": [], "dataset_name": "autoevaluate/xsum-sample", "dataset_config": "autoevaluate--xsum-sample", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}} | 2022-11-21T14:35:26+00:00 |
46db4b474918671e3a3a724a45cbed26d2c29e11 | # Dataset Card for "un_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | MikCil/un_dataset | [
"region:us"
] | 2022-11-21T14:44:54+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "caption", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 462328883.0, "num_examples": 904}, {"name": "validation", "num_bytes": 462328883.0, "num_examples": 904}], "download_size": 924654154, "dataset_size": 924657766.0}} | 2022-11-21T14:45:38+00:00 |
d69cafc5e82166290baea1a5a500a679d52d136a | # 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: autoevaluate/summarization
* Dataset: autoevaluate/xsum-sample
* Config: autoevaluate--xsum-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-71db21e5-84e8-4c03-8b5c-360b48e9252b-6463 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:45:33+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/xsum-sample"], "eval_info": {"task": "summarization", "model": "autoevaluate/summarization", "metrics": [], "dataset_name": "autoevaluate/xsum-sample", "dataset_config": "autoevaluate--xsum-sample", "dataset_split": "test", "col_mapping": {"text": "document", "target": "summary"}}} | 2022-11-21T14:46:06+00:00 |
d61906525b859c05cae3fce0e2e7f4a6727de7fb | # 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: autoevaluate/translation
* Dataset: autoevaluate/wmt16-ro-en-sample
* Config: autoevaluate--wmt16-ro-en-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | autoevaluate/autoeval-staging-eval-project-b07c55ed-3514-4853-9004-f2d3a7737d92-6564 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:48:30+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["autoevaluate/wmt16-ro-en-sample"], "eval_info": {"task": "translation", "model": "autoevaluate/translation", "metrics": [], "dataset_name": "autoevaluate/wmt16-ro-en-sample", "dataset_config": "autoevaluate--wmt16-ro-en-sample", "dataset_split": "test", "col_mapping": {"source": "translation.ro", "target": "translation.en"}}} | 2022-11-21T14:49:16+00:00 |
875de01ed5e2bbf6860b847bd91cc01ef198eb74 |
# Dataset Card for Brazilian Portuguese Sentiment Analysis Dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [Kaggle Dataset](https://www.kaggle.com/datasets/fredericods/ptbr-sentiment-analysis-datasets)
- **Paper:** [Sentiment Analysis on Brazilian Portuguese User Reviews](https://ieeexplore.ieee.org/abstract/document/9769838)
- **Point of Contact:** [Frederico Dias Souza]([email protected])
### Dataset Summary
**Disclaimer:** *The team releasing the dataset did not write a dataset card
for this dataset so this dataset card has been written by the contributors.*
The Brazilian Portuguese Sentiment Analysis Dataset (BPSAD) is composed
by the concatenation of 5 differents sources (Olist, B2W Digital, Buscapé,
UTLC-Apps and UTLC-Movies), each one is composed by evaluation sentences
classified according to the polarity (0: negative; 1: positive) and ratings
(1, 2, 3, 4 and 5 stars).
This dataset requires manual download:
1. Download the `concatenated` file from dataset homepage.
2. Extract the file inside `<path/to/manual/data>`.
3. Load the dataset using the command:
```python
datasets.load_dataset(
path="lm4pt/bpsad",
name='<polarity|rating>',
data_dir='<path/to/manual/data>')
```
A detailed description about the dataset and the processing steps can be
found at the [dataset homepage](https://www.kaggle.com/datasets/fredericods/ptbr-sentiment-analysis-datasets).
### Supported Tasks and Leaderboards
The dataset contains two configurations that represents the possible tasks
related to sentiment analysis. The polarity classification is a binary
classification problem where the sentences must be classified as positive (1)
or negative (0) reviews. The rating prediction is a multiclass problem
with values ranging from 1 to 5 stars.
### Languages
The texts are in Brazilian Portuguese, as spoken by users of different e-commerces and Filmow social network.
## Dataset Structure
### Data Instances
#### polarity
```
{
"review_text": "Bem macio e felpudo...recomendo. Preço imbatível e entrega rápida. Compraria outro quando precisar",
"polarity": 1
}
```
#### rating
```
{
"review_text": "Bem macio e felpudo...recomendo. Preço imbatível e entrega rápida. Compraria outro quando precisar",
"rating": 4
}
```
### Data Fields
#### polarity
- `review_text`: a `string` feature with product or movie review.
- `polarity`: an `integer` value that represents positive (1) or negative (0) reviews.
#### rating
- `review_text`: a `string` feature with product or movie review.
- `rating`: an `integer` value that represents the number of stars given by the reviewer. Possible values are 1, 2, 3, 4 and 5.
### Data Splits
Data splits are created based on the original `kfold` column of each configuration, following the original authors recomendations:
- train: folds 1 to 8
- validation: fold 9
- test: fold 10
| | train | validation | test |
|----------|--------:|-----------:|-------:|
| polarity | 1908937 | 238614 | 238613 |
| rating | 2228877 | 278608 | 278607 |
More information about sentence size and label distribution can be found in the [dataset homepage](https://www.kaggle.com/datasets/fredericods/ptbr-sentiment-analysis-datasets).
## 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
```
@inproceedings{souza2021sentiment,
author={
Souza, Frederico Dias and
Baptista de Oliveira e Souza Filho, João},
booktitle={
2021 IEEE Latin American Conference on
Computational Intelligence (LA-CCI)},
title={
Sentiment Analysis on Brazilian Portuguese User Reviews},
year={2021},
pages={1-6},
doi={10.1109/LA-CCI48322.2021.9769838}
}
```
### Contributions
Thanks to [@guilhermelmello](https://huggingface.co/guilhermelmello) and [@DominguesPH](https://huggingface.co/DominguesPH) for adding this dataset. | lm4pt/bpsad | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"task_ids:sentiment-analysis",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"language:pt",
"license:unknown",
"region:us"
] | 2022-11-21T15:37:12+00:00 | {"annotations_creators": [], "language_creators": ["other"], "language": ["pt"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": [], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification", "sentiment-classification", "sentiment-scoring", "sentiment-analysis"], "pretty_name": "bpsad", "tags": []} | 2022-11-23T19:20:11+00:00 |
ce6b3a39998f0305e850513643bd4b9ca80c74d4 | atokforps/test_data | [
"license:other",
"region:us"
] | 2022-11-21T16:13:13+00:00 | {"license": "other"} | 2022-11-21T16:30:33+00:00 |
|
cddd3191b81a031a606b27e8800d91105b5675c5 | nkandpa2/qa_entities | [
"license:bigscience-openrail-m",
"region:us"
] | 2022-11-21T16:28:21+00:00 | {"license": "bigscience-openrail-m"} | 2022-11-21T17:04:24+00:00 |
|
5aba6e36e57ad9618d0643c71876a1680b33aaa6 | # Dataset Card for "auto-mpg-split"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | dvgodoy/auto-mpg-split | [
"region:us"
] | 2022-11-21T16:28:39+00:00 | {"dataset_info": {"features": [{"name": "mpg", "dtype": "float64"}, {"name": "cylinders", "dtype": "int64"}, {"name": "displacement", "dtype": "float64"}, {"name": "horsepower", "dtype": "float64"}, {"name": "weight", "dtype": "int64"}, {"name": "acceleration", "dtype": "float64"}, {"name": "model year", "dtype": "int64"}, {"name": "origin", "dtype": "int64"}, {"name": "car name", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 26742.361809045226, "num_examples": 318}, {"name": "test", "num_bytes": 3363.819095477387, "num_examples": 40}, {"name": "valid", "num_bytes": 3363.819095477387, "num_examples": 40}], "download_size": 22370, "dataset_size": 33470.0}} | 2022-11-21T16:46:31+00:00 |
81b906121415bf962f67cec454b5ff5b56ae390a | # Dataset Card for "auto-mpg"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | dvgodoy/auto-mpg | [
"region:us"
] | 2022-11-21T16:37:13+00:00 | {"dataset_info": {"features": [{"name": "mpg", "dtype": "float64"}, {"name": "cylinders", "dtype": "int64"}, {"name": "displacement", "dtype": "float64"}, {"name": "horsepower", "dtype": "float64"}, {"name": "weight", "dtype": "int64"}, {"name": "acceleration", "dtype": "float64"}, {"name": "model year", "dtype": "int64"}, {"name": "origin", "dtype": "int64"}, {"name": "car name", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 33470, "num_examples": 398}], "download_size": 13036, "dataset_size": 33470}} | 2022-11-21T16:45:37+00:00 |
8b9a613ddc7d3f33e36732d9a1f2c283e4080ced | mcrovero/icons | [
"license:gpl",
"region:us"
] | 2022-11-21T17:11:10+00:00 | {"license": "gpl"} | 2022-11-21T17:14:38+00:00 |
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