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owanr/ghc-roberta-base-intra-data-frequency-model_annots_alpha0.8_whole_1e-05
|
owanr
| 2023-12-16T08:39:01Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"region:us"
] | null | 2023-12-15T16:07:43Z |
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: ghc-roberta-base-intra-data-frequency-model_annots_alpha0.8_whole_1e-05
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ghc-roberta-base-intra-data-frequency-model_annots_alpha0.8_whole_1e-05
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8783
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.7506 | 1.0 | 11020 | 1.9616 |
| 1.7737 | 2.0 | 22040 | 1.8783 |
| 1.8491 | 3.0 | 33060 | 1.8783 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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] |
Jeevesh8/bt__qqp_ft_only_data_shuff_17
|
Jeevesh8
| 2023-12-15T18:55:15Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T16:09:22Z |
Entry not found
|
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] |
Jeevesh8/bt__qqp_ft_only_data_shuff_16
|
Jeevesh8
| 2023-12-15T18:55:12Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T16:09:22Z |
Entry not found
|
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] |
Jeevesh8/bt__qqp_ft_only_data_shuff_19
|
Jeevesh8
| 2023-12-15T18:49:40Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T16:11:27Z |
Entry not found
|
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] |
Jeevesh8/bt__qqp_ft_only_data_shuff_18
|
Jeevesh8
| 2023-12-15T18:58:35Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T16:11:27Z |
Entry not found
|
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lazed-outt-for-real24/2009Janet
|
lazed-outt-for-real24
| 2023-12-15T16:13:13Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-15T16:11:27Z |
---
license: openrail
---
|
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] |
dvshah13/Reinforce-v2
|
dvshah13
| 2023-12-15T16:11:56Z | 0 | 0 | null |
[
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] |
reinforcement-learning
| 2023-12-15T16:11:38Z |
---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-pixelcopter
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:
- type: mean_reward
value: 62.30 +/- 56.21
name: mean_reward
verified: false
---
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
|
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] |
AleRams/app_prova2
|
AleRams
| 2023-12-15T17:52:31Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:bert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T16:13:46Z |
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: app_prova2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# app_prova2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0814
- Accuracy: 0.684
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6449 | 0.08 | 10 | 1.4346 | 0.634 |
| 1.2571 | 0.16 | 20 | 1.2345 | 0.636 |
| 1.2195 | 0.24 | 30 | 1.1756 | 0.636 |
| 1.3451 | 0.32 | 40 | 1.1500 | 0.636 |
| 1.328 | 0.4 | 50 | 1.1456 | 0.636 |
| 1.0584 | 0.48 | 60 | 1.1726 | 0.636 |
| 1.1234 | 0.56 | 70 | 1.1935 | 0.636 |
| 1.1307 | 0.64 | 80 | 1.1132 | 0.636 |
| 1.0517 | 0.72 | 90 | 1.1070 | 0.636 |
| 1.0545 | 0.8 | 100 | 1.1493 | 0.636 |
| 1.1644 | 0.88 | 110 | 1.0946 | 0.635 |
| 1.205 | 0.96 | 120 | 1.0881 | 0.633 |
| 1.0908 | 1.04 | 130 | 1.1057 | 0.636 |
| 1.1017 | 1.12 | 140 | 1.0926 | 0.633 |
| 1.0318 | 1.2 | 150 | 1.1040 | 0.633 |
| 1.1105 | 1.28 | 160 | 1.0895 | 0.633 |
| 1.0025 | 1.36 | 170 | 1.0888 | 0.635 |
| 0.8336 | 1.44 | 180 | 1.1101 | 0.633 |
| 0.9042 | 1.52 | 190 | 1.1572 | 0.635 |
| 1.0081 | 1.6 | 200 | 1.0749 | 0.645 |
| 0.842 | 1.68 | 210 | 1.0747 | 0.661 |
| 0.9901 | 1.76 | 220 | 1.0882 | 0.67 |
| 1.0027 | 1.84 | 230 | 1.0805 | 0.673 |
| 0.8014 | 1.92 | 240 | 1.0784 | 0.671 |
| 0.7624 | 2.0 | 250 | 1.0789 | 0.674 |
| 0.9224 | 2.08 | 260 | 1.0733 | 0.677 |
| 0.8121 | 2.16 | 270 | 1.0579 | 0.689 |
| 0.8098 | 2.24 | 280 | 1.0757 | 0.681 |
| 0.8758 | 2.32 | 290 | 1.0698 | 0.685 |
| 0.877 | 2.4 | 300 | 1.0613 | 0.687 |
| 0.8596 | 2.48 | 310 | 1.0559 | 0.688 |
| 0.7192 | 2.56 | 320 | 1.0642 | 0.687 |
| 0.6199 | 2.64 | 330 | 1.0845 | 0.682 |
| 0.7999 | 2.72 | 340 | 1.0909 | 0.681 |
| 0.6764 | 2.8 | 350 | 1.0944 | 0.68 |
| 0.8604 | 2.88 | 360 | 1.0873 | 0.684 |
| 0.7477 | 2.96 | 370 | 1.0814 | 0.684 |
### Framework versions
- Transformers 4.36.1
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned-adapters_humanMix_Seed103
|
behzadnet
| 2023-12-15T16:13:58Z | 0 | 0 |
peft
|
[
"peft",
"arxiv:1910.09700",
"base_model:Trelis/Llama-2-7b-chat-hf-sharded-bf16",
"region:us"
] | null | 2023-12-15T16:13:52Z |
---
library_name: peft
base_model: Trelis/Llama-2-7b-chat-hf-sharded-bf16
---
# Model Card for Model ID
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## Model Details
### Model Description
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## How to Get Started with the Model
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## Training Details
### Training Data
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### Training Procedure
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#### Preprocessing [optional]
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#### Training Hyperparameters
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## Environmental Impact
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.7.0.dev0
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.7.0.dev0
|
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behzadnet/Llama-2-7b-chat-hf-sharded-bf16-fine-tuned_humanMix_Seed103
|
behzadnet
| 2023-12-15T16:14:08Z | 0 | 0 |
peft
|
[
"peft",
"arxiv:1910.09700",
"base_model:Trelis/Llama-2-7b-chat-hf-sharded-bf16",
"region:us"
] | null | 2023-12-15T16:14:05Z |
---
library_name: peft
base_model: Trelis/Llama-2-7b-chat-hf-sharded-bf16
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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- **Developed by:** [More Information Needed]
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## How to Get Started with the Model
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## Training Details
### Training Data
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### Training Procedure
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#### Preprocessing [optional]
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#### Training Hyperparameters
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#### Metrics
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### Results
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#### Summary
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## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.7.0.dev0
|
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] |
VishalMysore/cookgptnano
|
VishalMysore
| 2023-12-15T16:14:26Z | 0 | 0 | null |
[
"autotrain",
"text-generation",
"region:us"
] |
text-generation
| 2023-12-15T16:14:20Z |
---
tags:
- autotrain
- text-generation
widget:
- text: "I love AutoTrain because "
---
# Model Trained Using AutoTrain
|
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syp1229/ctc-cstom-tokenizer-test
|
syp1229
| 2023-12-15T16:15:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:15:53Z |
Entry not found
|
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D-rkMatter/my_awesome_eli5_mlm_model
|
D-rkMatter
| 2023-12-15T16:16:12Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:16:12Z |
Entry not found
|
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] |
thorirhrafn/llama2_lora_ice
|
thorirhrafn
| 2023-12-16T09:24:32Z | 0 | 0 | null |
[
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-hf",
"region:us"
] | null | 2023-12-15T16:18:34Z |
---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama2_lora_ice
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama2_lora_ice
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9765
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 100000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 2.2437 | 0.19 | 5000 | 2.2019 |
| 2.2007 | 0.38 | 10000 | 2.1012 |
| 2.1122 | 0.57 | 15000 | 2.0569 |
| 2.0245 | 0.75 | 20000 | 2.0304 |
| 2.0999 | 0.94 | 25000 | 2.0149 |
| 2.0091 | 1.13 | 30000 | 2.0047 |
| 2.0459 | 1.32 | 35000 | 1.9975 |
| 2.0464 | 1.51 | 40000 | 1.9912 |
| 1.9638 | 1.7 | 45000 | 1.9869 |
| 2.0021 | 1.88 | 50000 | 1.9836 |
| 2.0201 | 2.07 | 55000 | 1.9819 |
| 2.0176 | 2.26 | 60000 | 1.9800 |
| 1.9951 | 2.45 | 65000 | 1.9789 |
| 2.0183 | 2.64 | 70000 | 1.9780 |
| 2.0013 | 2.83 | 75000 | 1.9773 |
| 2.0242 | 3.02 | 80000 | 1.9769 |
| 1.9803 | 3.2 | 85000 | 1.9766 |
| 2.0179 | 3.39 | 90000 | 1.9766 |
| 1.9712 | 3.58 | 95000 | 1.9765 |
| 2.0008 | 3.77 | 100000 | 1.9765 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
|
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] |
ownimage/t5-small-finetuned-xsum
|
ownimage
| 2023-12-17T17:01:45Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:xsum",
"base_model:t5-small",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text2text-generation
| 2023-12-15T16:19:02Z |
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 28.2579
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-xsum
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4781
- Rouge1: 28.2579
- Rouge2: 7.7294
- Rougel: 22.2389
- Rougelsum: 22.2421
- Gen Len: 18.8265
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.7085 | 1.0 | 12753 | 2.4781 | 28.2579 | 7.7294 | 22.2389 | 22.2421 | 18.8265 |
### Framework versions
- Transformers 4.36.1
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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simecek/cswikimistral_0.1-gguf
|
simecek
| 2023-12-15T16:35:43Z | 0 | 0 | null |
[
"gguf",
"region:us"
] | null | 2023-12-15T16:19:41Z |
Entry not found
|
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] |
Tsuinzues/spencer
|
Tsuinzues
| 2023-12-15T16:21:17Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-15T16:21:01Z |
---
license: openrail
---
|
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dvshah13/poca-SoccerTwos
|
dvshah13
| 2023-12-15T16:24:24Z | 0 | 0 |
ml-agents
|
[
"ml-agents",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] |
reinforcement-learning
| 2023-12-15T16:23:22Z |
---
library_name: ml-agents
tags:
- SoccerTwos
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
- A *longer tutorial* to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
### Resume the training
```bash
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser**
1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: dvshah13/poca-SoccerTwos
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
|
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digitalinsanity/Breen_hl2
|
digitalinsanity
| 2023-12-15T16:25:05Z | 0 | 0 | null |
[
"license:cc-by-nc-nd-4.0",
"region:us"
] | null | 2023-12-15T16:23:49Z |
---
license: cc-by-nc-nd-4.0
---
|
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] |
sanghyo/Final_model2
|
sanghyo
| 2023-12-15T19:33:43Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"bart",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2023-12-15T16:24:40Z |
Entry not found
|
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] |
PeterV09/mistral-7b-300k-10k-a100-6e-valid
|
PeterV09
| 2023-12-15T16:33:51Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"mistral",
"text-generation",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-12-15T16:25:26Z |
---
tags:
- generated_from_trainer
model-index:
- name: mistral-7b-300k-10k-a100-6e-valid
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral-7b-300k-10k-a100-6e-valid
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 128
- total_train_batch_size: 512
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0
### Training results
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
|
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] |
AmanMussa/llama2-fake-news-detection-7b
|
AmanMussa
| 2023-12-15T18:35:14Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"llama",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-12-15T16:25:35Z |
Entry not found
|
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] |
hkivancoral/smids_5x_deit_tiny_sgd_0001_fold5
|
hkivancoral
| 2023-12-15T17:24:42Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:facebook/deit-tiny-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-15T16:30:13Z |
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_tiny_sgd_0001_fold5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8216666666666667
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smids_5x_deit_tiny_sgd_0001_fold5
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4623
- Accuracy: 0.8217
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1763 | 1.0 | 375 | 1.1547 | 0.3917 |
| 1.0966 | 2.0 | 750 | 1.0897 | 0.42 |
| 1.0223 | 3.0 | 1125 | 1.0444 | 0.46 |
| 0.9886 | 4.0 | 1500 | 1.0052 | 0.4917 |
| 0.9546 | 5.0 | 1875 | 0.9693 | 0.515 |
| 0.932 | 6.0 | 2250 | 0.9344 | 0.54 |
| 0.8619 | 7.0 | 2625 | 0.9000 | 0.57 |
| 0.857 | 8.0 | 3000 | 0.8647 | 0.5967 |
| 0.8079 | 9.0 | 3375 | 0.8304 | 0.62 |
| 0.7619 | 10.0 | 3750 | 0.7976 | 0.645 |
| 0.7316 | 11.0 | 4125 | 0.7657 | 0.665 |
| 0.6666 | 12.0 | 4500 | 0.7355 | 0.68 |
| 0.6961 | 13.0 | 4875 | 0.7078 | 0.69 |
| 0.6607 | 14.0 | 5250 | 0.6819 | 0.7083 |
| 0.6448 | 15.0 | 5625 | 0.6579 | 0.725 |
| 0.6031 | 16.0 | 6000 | 0.6371 | 0.7333 |
| 0.633 | 17.0 | 6375 | 0.6195 | 0.7433 |
| 0.6177 | 18.0 | 6750 | 0.6022 | 0.7533 |
| 0.5854 | 19.0 | 7125 | 0.5875 | 0.765 |
| 0.5213 | 20.0 | 7500 | 0.5748 | 0.77 |
| 0.5296 | 21.0 | 7875 | 0.5628 | 0.7833 |
| 0.5226 | 22.0 | 8250 | 0.5527 | 0.7917 |
| 0.5777 | 23.0 | 8625 | 0.5439 | 0.795 |
| 0.5616 | 24.0 | 9000 | 0.5354 | 0.8017 |
| 0.5254 | 25.0 | 9375 | 0.5279 | 0.8067 |
| 0.5443 | 26.0 | 9750 | 0.5213 | 0.8067 |
| 0.5349 | 27.0 | 10125 | 0.5152 | 0.8133 |
| 0.5476 | 28.0 | 10500 | 0.5090 | 0.8133 |
| 0.5198 | 29.0 | 10875 | 0.5041 | 0.815 |
| 0.4665 | 30.0 | 11250 | 0.4997 | 0.8167 |
| 0.5013 | 31.0 | 11625 | 0.4955 | 0.8167 |
| 0.5242 | 32.0 | 12000 | 0.4917 | 0.8167 |
| 0.5162 | 33.0 | 12375 | 0.4881 | 0.8167 |
| 0.5094 | 34.0 | 12750 | 0.4847 | 0.815 |
| 0.4537 | 35.0 | 13125 | 0.4817 | 0.8167 |
| 0.4056 | 36.0 | 13500 | 0.4788 | 0.8167 |
| 0.4566 | 37.0 | 13875 | 0.4763 | 0.8167 |
| 0.4864 | 38.0 | 14250 | 0.4740 | 0.8183 |
| 0.4572 | 39.0 | 14625 | 0.4721 | 0.82 |
| 0.5272 | 40.0 | 15000 | 0.4702 | 0.82 |
| 0.4662 | 41.0 | 15375 | 0.4685 | 0.82 |
| 0.4598 | 42.0 | 15750 | 0.4671 | 0.82 |
| 0.4764 | 43.0 | 16125 | 0.4660 | 0.82 |
| 0.4497 | 44.0 | 16500 | 0.4650 | 0.82 |
| 0.4734 | 45.0 | 16875 | 0.4641 | 0.82 |
| 0.4953 | 46.0 | 17250 | 0.4634 | 0.82 |
| 0.4817 | 47.0 | 17625 | 0.4629 | 0.8217 |
| 0.4691 | 48.0 | 18000 | 0.4625 | 0.8217 |
| 0.4502 | 49.0 | 18375 | 0.4623 | 0.8217 |
| 0.4257 | 50.0 | 18750 | 0.4623 | 0.8217 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|
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yihang7/zephyr-7b-dpo-full
|
yihang7
| 2023-12-15T16:30:52Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:30:52Z |
Entry not found
|
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] |
dvshah13/dhbert-finetuned-gtzan
|
dvshah13
| 2023-12-15T16:37:07Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"audio-spectrogram-transformer",
"audio-classification",
"generated_from_trainer",
"dataset:marsyas/gtzan",
"license:bsd-3-clause",
"model-index",
"endpoints_compatible",
"region:us"
] |
audio-classification
| 2023-12-15T16:31:45Z |
---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.9
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4717
- Accuracy: 0.9
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7581 | 1.0 | 56 | 0.7029 | 0.78 |
| 0.3942 | 1.99 | 112 | 0.4646 | 0.86 |
| 0.3298 | 2.99 | 168 | 0.3861 | 0.88 |
| 0.1227 | 4.0 | 225 | 0.4702 | 0.86 |
| 0.0774 | 5.0 | 281 | 0.4492 | 0.9 |
| 0.0039 | 5.99 | 337 | 0.4607 | 0.9 |
| 0.0014 | 6.99 | 393 | 0.5022 | 0.9 |
| 0.0022 | 8.0 | 450 | 0.4711 | 0.9 |
| 0.0193 | 9.0 | 506 | 0.5226 | 0.86 |
| 0.0004 | 9.99 | 562 | 0.6055 | 0.82 |
| 0.0003 | 10.99 | 618 | 0.4793 | 0.89 |
| 0.0002 | 12.0 | 675 | 0.5052 | 0.9 |
| 0.0002 | 13.0 | 731 | 0.4652 | 0.89 |
| 0.0001 | 13.99 | 787 | 0.4617 | 0.9 |
| 0.0001 | 14.99 | 843 | 0.4653 | 0.9 |
| 0.0001 | 16.0 | 900 | 0.4635 | 0.91 |
| 0.0001 | 17.0 | 956 | 0.4693 | 0.9 |
| 0.0001 | 17.99 | 1012 | 0.4697 | 0.9 |
| 0.0001 | 18.99 | 1068 | 0.4715 | 0.9 |
| 0.0025 | 19.91 | 1120 | 0.4717 | 0.9 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|
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] |
yu7400ki/candle-opusmt
|
yu7400ki
| 2023-12-17T15:57:27Z | 0 | 0 | null |
[
"safetensors",
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T16:33:56Z |
---
license: apache-2.0
---
|
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phrygiangates/codeparrot-ds
|
phrygiangates
| 2023-12-15T16:34:03Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:34:03Z |
Entry not found
|
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syp1229/CTC-test
|
syp1229
| 2023-12-15T16:36:29Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:36:29Z |
Entry not found
|
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JackJantzi/chatbot
|
JackJantzi
| 2023-12-15T16:36:30Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:36:30Z |
Entry not found
|
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Jinpf314/Jinpf314
|
Jinpf314
| 2023-12-15T16:36:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:36:59Z |
Entry not found
|
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-0.17026887834072113,
0.26989826560020447,
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-0.028933173045516014,
-0.05796251446008682,
0.31015992164611816,
-1.0262157917022705
] |
Zilun/GeoRSSD
|
Zilun
| 2023-12-16T15:17:55Z | 0 | 0 |
diffusers
|
[
"diffusers",
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T16:39:00Z |
---
license: apache-2.0
---
# GeoRSSD
* Stable Diffusion fine-tuned by RS5M (1% data)
**Please refer to [this repo](https://github.com/ShivamShrirao/diffusers/tree/main/examples/dreambooth) for using checkpoint to inference.**
|
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AAVERSANO/ANGELOAI2
|
AAVERSANO
| 2023-12-15T16:41:04Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:39:46Z |
Entry not found
|
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] |
Nvatomate/LLM1
|
Nvatomate
| 2023-12-15T16:39:48Z | 0 | 0 | null |
[
"license:gpl-3.0",
"region:us"
] | null | 2023-12-15T16:39:48Z |
---
license: gpl-3.0
---
|
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viktor-shevchuk/bart-large-cnn-finetuned-laws_articles
|
viktor-shevchuk
| 2023-12-15T23:18:50Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/bart-large-cnn",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2023-12-15T16:40:33Z |
---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-laws_articles
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart-large-cnn-finetuned-laws_articles
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2619
- Rouge1: 37.4577
- Rouge2: 17.4395
- Rougel: 27.6576
- Rougelsum: 29.1109
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log | 1.0 | 86 | 1.9613 | 40.6402 | 20.5834 | 31.9641 | 33.0747 |
| No log | 1.99 | 172 | 2.0573 | 39.7679 | 19.7934 | 29.9615 | 31.2392 |
| No log | 3.0 | 259 | 2.1328 | 38.2225 | 18.195 | 28.8951 | 30.4138 |
| No log | 3.99 | 345 | 2.2619 | 37.4577 | 17.4395 | 27.6576 | 29.1109 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.14.1
|
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] |
dvshah13/whisper-tiny
|
dvshah13
| 2023-12-15T16:41:01Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:PolyAI/minds14",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2023-12-15T16:40:35Z |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train[450:]
args: en-US
metrics:
- name: Wer
type: wer
value: 0.33943329397874855
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-tiny
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6844
- Wer Ortho: 0.3424
- Wer: 0.3394
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0006 | 17.86 | 500 | 0.6844 | 0.3424 | 0.3394 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|
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] |
h4iku/codet5-small-t5apr-python
|
h4iku
| 2023-12-16T05:10:54Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text2text-generation
| 2023-12-15T16:40:55Z |
Entry not found
|
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StatsGary/mistral7B-ft-guanaco-llama2-1k
|
StatsGary
| 2023-12-15T16:47:20Z | 0 | 0 |
peft
|
[
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:mistralai/Mistral-7B-Instruct-v0.1",
"region:us"
] | null | 2023-12-15T16:46:50Z |
---
library_name: peft
base_model: mistralai/Mistral-7B-Instruct-v0.1
---
# Model Card for Model ID
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## Model Details
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<!-- Relevant interpretability work for the model goes here -->
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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## Model Card Contact
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### Framework versions
- PEFT 0.7.1
|
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] |
hkivancoral/smids_5x_beit_base_sgd_0001_fold4
|
hkivancoral
| 2023-12-15T18:05:59Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-15T16:47:02Z |
---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_beit_base_sgd_0001_fold4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7983333333333333
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smids_5x_beit_base_sgd_0001_fold4
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4817
- Accuracy: 0.7983
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1553 | 1.0 | 375 | 1.2548 | 0.355 |
| 1.0974 | 2.0 | 750 | 1.1671 | 0.3783 |
| 0.9812 | 3.0 | 1125 | 1.0817 | 0.4167 |
| 0.9358 | 4.0 | 1500 | 1.0016 | 0.455 |
| 0.8746 | 5.0 | 1875 | 0.9264 | 0.53 |
| 0.8021 | 6.0 | 2250 | 0.8621 | 0.5983 |
| 0.7908 | 7.0 | 2625 | 0.8069 | 0.6717 |
| 0.763 | 8.0 | 3000 | 0.7629 | 0.69 |
| 0.6997 | 9.0 | 3375 | 0.7270 | 0.7133 |
| 0.6962 | 10.0 | 3750 | 0.6950 | 0.7167 |
| 0.6391 | 11.0 | 4125 | 0.6689 | 0.7283 |
| 0.6231 | 12.0 | 4500 | 0.6467 | 0.735 |
| 0.6127 | 13.0 | 4875 | 0.6274 | 0.7483 |
| 0.6297 | 14.0 | 5250 | 0.6106 | 0.7517 |
| 0.6056 | 15.0 | 5625 | 0.5959 | 0.7633 |
| 0.5383 | 16.0 | 6000 | 0.5842 | 0.76 |
| 0.5862 | 17.0 | 6375 | 0.5727 | 0.76 |
| 0.5466 | 18.0 | 6750 | 0.5631 | 0.7683 |
| 0.6063 | 19.0 | 7125 | 0.5554 | 0.77 |
| 0.5382 | 20.0 | 7500 | 0.5477 | 0.7733 |
| 0.5719 | 21.0 | 7875 | 0.5406 | 0.7733 |
| 0.5194 | 22.0 | 8250 | 0.5342 | 0.7833 |
| 0.5408 | 23.0 | 8625 | 0.5290 | 0.7833 |
| 0.5327 | 24.0 | 9000 | 0.5248 | 0.7817 |
| 0.5341 | 25.0 | 9375 | 0.5207 | 0.7833 |
| 0.5248 | 26.0 | 9750 | 0.5168 | 0.7833 |
| 0.5823 | 27.0 | 10125 | 0.5128 | 0.7867 |
| 0.4919 | 28.0 | 10500 | 0.5098 | 0.79 |
| 0.4902 | 29.0 | 10875 | 0.5067 | 0.7933 |
| 0.5047 | 30.0 | 11250 | 0.5038 | 0.795 |
| 0.4943 | 31.0 | 11625 | 0.5008 | 0.7983 |
| 0.5058 | 32.0 | 12000 | 0.4990 | 0.7983 |
| 0.4976 | 33.0 | 12375 | 0.4965 | 0.7967 |
| 0.5168 | 34.0 | 12750 | 0.4952 | 0.795 |
| 0.5069 | 35.0 | 13125 | 0.4933 | 0.795 |
| 0.4844 | 36.0 | 13500 | 0.4915 | 0.7967 |
| 0.5181 | 37.0 | 13875 | 0.4900 | 0.7983 |
| 0.5125 | 38.0 | 14250 | 0.4886 | 0.7983 |
| 0.5414 | 39.0 | 14625 | 0.4875 | 0.7983 |
| 0.5265 | 40.0 | 15000 | 0.4865 | 0.7983 |
| 0.5089 | 41.0 | 15375 | 0.4855 | 0.7983 |
| 0.5041 | 42.0 | 15750 | 0.4845 | 0.7983 |
| 0.5029 | 43.0 | 16125 | 0.4836 | 0.7983 |
| 0.4723 | 44.0 | 16500 | 0.4830 | 0.7983 |
| 0.4754 | 45.0 | 16875 | 0.4827 | 0.7983 |
| 0.4906 | 46.0 | 17250 | 0.4823 | 0.7983 |
| 0.5249 | 47.0 | 17625 | 0.4820 | 0.7983 |
| 0.4858 | 48.0 | 18000 | 0.4818 | 0.7983 |
| 0.4635 | 49.0 | 18375 | 0.4818 | 0.7983 |
| 0.4753 | 50.0 | 18750 | 0.4817 | 0.7983 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|
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hkivancoral/smids_5x_beit_base_sgd_001_fold4
|
hkivancoral
| 2023-12-15T18:06:02Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-15T16:47:08Z |
---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_beit_base_sgd_001_fold4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8466666666666667
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smids_5x_beit_base_sgd_001_fold4
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4156
- Accuracy: 0.8467
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6893 | 1.0 | 375 | 0.6764 | 0.7333 |
| 0.5522 | 2.0 | 750 | 0.5194 | 0.7917 |
| 0.409 | 3.0 | 1125 | 0.4634 | 0.805 |
| 0.4507 | 4.0 | 1500 | 0.4337 | 0.81 |
| 0.416 | 5.0 | 1875 | 0.4157 | 0.8233 |
| 0.3067 | 6.0 | 2250 | 0.4110 | 0.825 |
| 0.3644 | 7.0 | 2625 | 0.3987 | 0.8333 |
| 0.3243 | 8.0 | 3000 | 0.3991 | 0.835 |
| 0.3062 | 9.0 | 3375 | 0.3919 | 0.8383 |
| 0.308 | 10.0 | 3750 | 0.3990 | 0.8383 |
| 0.2735 | 11.0 | 4125 | 0.3981 | 0.835 |
| 0.2384 | 12.0 | 4500 | 0.3880 | 0.8417 |
| 0.2357 | 13.0 | 4875 | 0.3907 | 0.845 |
| 0.3175 | 14.0 | 5250 | 0.3900 | 0.8417 |
| 0.2423 | 15.0 | 5625 | 0.3853 | 0.8517 |
| 0.1987 | 16.0 | 6000 | 0.3848 | 0.8433 |
| 0.2594 | 17.0 | 6375 | 0.3874 | 0.845 |
| 0.2225 | 18.0 | 6750 | 0.3883 | 0.8533 |
| 0.247 | 19.0 | 7125 | 0.3920 | 0.8383 |
| 0.2235 | 20.0 | 7500 | 0.3894 | 0.8433 |
| 0.2203 | 21.0 | 7875 | 0.3971 | 0.8417 |
| 0.2258 | 22.0 | 8250 | 0.3954 | 0.8533 |
| 0.2363 | 23.0 | 8625 | 0.3968 | 0.845 |
| 0.2288 | 24.0 | 9000 | 0.3993 | 0.8467 |
| 0.2646 | 25.0 | 9375 | 0.4039 | 0.84 |
| 0.1839 | 26.0 | 9750 | 0.3987 | 0.8433 |
| 0.2779 | 27.0 | 10125 | 0.4000 | 0.845 |
| 0.1848 | 28.0 | 10500 | 0.4019 | 0.8367 |
| 0.2029 | 29.0 | 10875 | 0.4110 | 0.84 |
| 0.2593 | 30.0 | 11250 | 0.4030 | 0.845 |
| 0.2187 | 31.0 | 11625 | 0.4051 | 0.8417 |
| 0.1821 | 32.0 | 12000 | 0.4072 | 0.8467 |
| 0.2095 | 33.0 | 12375 | 0.4076 | 0.8433 |
| 0.2109 | 34.0 | 12750 | 0.4087 | 0.8433 |
| 0.1759 | 35.0 | 13125 | 0.4129 | 0.84 |
| 0.1595 | 36.0 | 13500 | 0.4130 | 0.8433 |
| 0.2131 | 37.0 | 13875 | 0.4150 | 0.84 |
| 0.2036 | 38.0 | 14250 | 0.4132 | 0.85 |
| 0.247 | 39.0 | 14625 | 0.4135 | 0.8433 |
| 0.2148 | 40.0 | 15000 | 0.4147 | 0.8433 |
| 0.2333 | 41.0 | 15375 | 0.4120 | 0.8433 |
| 0.213 | 42.0 | 15750 | 0.4128 | 0.8433 |
| 0.1929 | 43.0 | 16125 | 0.4163 | 0.84 |
| 0.1822 | 44.0 | 16500 | 0.4161 | 0.845 |
| 0.2316 | 45.0 | 16875 | 0.4158 | 0.845 |
| 0.1873 | 46.0 | 17250 | 0.4147 | 0.845 |
| 0.2645 | 47.0 | 17625 | 0.4157 | 0.845 |
| 0.1954 | 48.0 | 18000 | 0.4157 | 0.845 |
| 0.1804 | 49.0 | 18375 | 0.4155 | 0.8467 |
| 0.1952 | 50.0 | 18750 | 0.4156 | 0.8467 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|
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] |
allstax/CodeExplainer-7b-v0.11-GPTQ
|
allstax
| 2023-12-16T14:22:21Z | 0 | 0 |
peft
|
[
"peft",
"safetensors",
"generated_from_trainer",
"base_model:TheBloke/Marcoroni-7B-v3-GPTQ",
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T16:50:07Z |
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Marcoroni-7B-v3-GPTQ
model-index:
- name: 20231215-144935
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 20231215-144935
This model is a fine-tuned version of [TheBloke/Marcoroni-7B-v3-GPTQ](https://huggingface.co/TheBloke/Marcoroni-7B-v3-GPTQ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2792
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1951 | 0.02 | 1 | 2.0427 |
| 1.4965 | 0.03 | 2 | 2.0427 |
| 2.2716 | 0.05 | 3 | 1.9661 |
| 1.9397 | 0.06 | 4 | 1.9661 |
| 1.8659 | 0.08 | 5 | 1.9661 |
| 1.9903 | 0.09 | 6 | 1.8551 |
| 1.9031 | 0.11 | 7 | 1.7846 |
| 1.929 | 0.12 | 8 | 1.7253 |
| 0.9994 | 0.14 | 9 | 1.6749 |
| 1.4887 | 0.15 | 10 | 1.6266 |
| 1.2112 | 0.17 | 11 | 1.5763 |
| 1.3437 | 0.18 | 12 | 1.5326 |
| 1.1061 | 0.2 | 13 | 1.5014 |
| 1.4769 | 0.22 | 14 | 1.4676 |
| 1.452 | 0.23 | 15 | 1.4313 |
| 1.2393 | 0.25 | 16 | 1.3963 |
| 1.1998 | 0.26 | 17 | 1.3662 |
| 1.529 | 0.28 | 18 | 1.3353 |
| 0.949 | 0.29 | 19 | 1.3088 |
| 1.1857 | 0.31 | 20 | 1.2798 |
| 1.4852 | 0.32 | 21 | 1.2484 |
| 1.2845 | 0.34 | 22 | 1.2146 |
| 1.332 | 0.35 | 23 | 1.1795 |
| 0.8718 | 0.37 | 24 | 1.1435 |
| 1.2038 | 0.38 | 25 | 1.1069 |
| 1.2105 | 0.4 | 26 | 1.0683 |
| 0.9161 | 0.42 | 27 | 1.0277 |
| 1.0415 | 0.43 | 28 | 0.9849 |
| 1.0367 | 0.45 | 29 | 0.9400 |
| 0.9279 | 0.46 | 30 | 0.8924 |
| 0.82 | 0.48 | 31 | 0.8467 |
| 0.8286 | 0.49 | 32 | 0.8077 |
| 0.7855 | 0.51 | 33 | 0.7645 |
| 0.7919 | 0.52 | 34 | 0.7164 |
| 0.6294 | 0.54 | 35 | 0.6712 |
| 0.6205 | 0.55 | 36 | 0.6302 |
| 0.5754 | 0.57 | 37 | 0.5926 |
| 0.6331 | 0.58 | 38 | 0.5578 |
| 0.5068 | 0.6 | 39 | 0.5251 |
| 0.5252 | 0.62 | 40 | 0.5009 |
| 0.442 | 0.63 | 41 | 0.4800 |
| 0.4451 | 0.65 | 42 | 0.4628 |
| 0.3742 | 0.66 | 43 | 0.4491 |
| 0.8263 | 0.68 | 44 | 0.4383 |
| 0.4392 | 0.69 | 45 | 0.4277 |
| 0.5359 | 0.71 | 46 | 0.4174 |
| 0.3903 | 0.72 | 47 | 0.4051 |
| 0.4177 | 0.74 | 48 | 0.3921 |
| 0.4606 | 0.75 | 49 | 0.3792 |
| 0.5233 | 0.77 | 50 | 0.3700 |
| 0.3838 | 0.78 | 51 | 0.3638 |
| 0.353 | 0.8 | 52 | 0.3587 |
| 0.3108 | 0.82 | 53 | 0.3530 |
| 0.4029 | 0.83 | 54 | 0.3470 |
| 0.3425 | 0.85 | 55 | 0.3411 |
| 0.2976 | 0.86 | 56 | 0.3345 |
| 0.5347 | 0.88 | 57 | 0.3291 |
| 0.3208 | 0.89 | 58 | 0.3239 |
| 0.3319 | 0.91 | 59 | 0.3194 |
| 0.3333 | 0.92 | 60 | 0.3160 |
| 0.3102 | 0.94 | 61 | 0.3135 |
| 0.4149 | 0.95 | 62 | 0.3118 |
| 0.3044 | 0.97 | 63 | 0.3098 |
| 0.2688 | 0.98 | 64 | 0.3076 |
| 0.3926 | 1.0 | 65 | 0.3060 |
| 0.2969 | 1.02 | 66 | 0.3045 |
| 0.3799 | 1.03 | 67 | 0.3029 |
| 0.3045 | 1.05 | 68 | 0.3014 |
| 0.2295 | 1.06 | 69 | 0.2997 |
| 0.4113 | 1.08 | 70 | 0.2983 |
| 0.3093 | 1.09 | 71 | 0.2969 |
| 0.2542 | 1.11 | 72 | 0.2957 |
| 0.2445 | 1.12 | 73 | 0.2947 |
| 0.2592 | 1.14 | 74 | 0.2935 |
| 0.6259 | 1.15 | 75 | 0.2925 |
| 0.3217 | 1.17 | 76 | 0.2916 |
| 0.2969 | 1.18 | 77 | 0.2907 |
| 0.287 | 1.2 | 78 | 0.2898 |
| 0.2642 | 1.22 | 79 | 0.2890 |
| 0.2735 | 1.23 | 80 | 0.2880 |
| 0.2472 | 1.25 | 81 | 0.2870 |
| 0.3068 | 1.26 | 82 | 0.2862 |
| 0.2779 | 1.28 | 83 | 0.2855 |
| 0.2915 | 1.29 | 84 | 0.2848 |
| 0.3926 | 1.31 | 85 | 0.2841 |
| 0.3057 | 1.32 | 86 | 0.2836 |
| 0.2413 | 1.34 | 87 | 0.2830 |
| 0.2851 | 1.35 | 88 | 0.2826 |
| 0.2295 | 1.37 | 89 | 0.2821 |
| 0.2611 | 1.38 | 90 | 0.2817 |
| 0.6346 | 1.4 | 91 | 0.2814 |
| 0.2297 | 1.42 | 92 | 0.2811 |
| 0.4868 | 1.43 | 93 | 0.2808 |
| 0.2819 | 1.45 | 94 | 0.2805 |
| 0.2589 | 1.46 | 95 | 0.2803 |
| 0.2171 | 1.48 | 96 | 0.2801 |
| 0.2581 | 1.49 | 97 | 0.2798 |
| 0.2495 | 1.51 | 98 | 0.2796 |
| 0.2702 | 1.52 | 99 | 0.2793 |
| 0.271 | 1.54 | 100 | 0.2792 |
### Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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RajuEEE/dialogue-summary-training-1702658865
|
RajuEEE
| 2023-12-15T16:50:33Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:50:33Z |
Entry not found
|
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mkim5052/test
|
mkim5052
| 2023-12-15T16:51:06Z | 0 | 0 | null |
[
"license:mit",
"region:us"
] | null | 2023-12-15T16:51:06Z |
---
license: mit
---
|
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Monkeydddd/unfortunate
|
Monkeydddd
| 2023-12-15T16:51:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:51:45Z |
Entry not found
|
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Amna100/output
|
Amna100
| 2023-12-15T16:51:49Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:51:49Z |
Entry not found
|
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] |
JACK666666/llm
|
JACK666666
| 2023-12-15T16:52:51Z | 0 | 0 | null |
[
"arxiv:1910.09700",
"region:us"
] | null | 2023-12-15T16:52:25Z |
---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
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{}
---
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|
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dbailleul/ppo-LunarLander-v2-unit8
|
dbailleul
| 2023-12-15T16:53:37Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:53:37Z |
Entry not found
|
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Jayakumar2023/Jaya
|
Jayakumar2023
| 2023-12-15T16:53:38Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T16:53:38Z |
Entry not found
|
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squidarth/sid-public
|
squidarth
| 2023-12-15T16:56:00Z | 0 | 0 | null |
[
"license:mit",
"region:us"
] | null | 2023-12-15T16:56:00Z |
---
license: mit
---
|
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] |
KathirKs/phi-2_lima_finetuned
|
KathirKs
| 2023-12-15T16:56:21Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T16:56:20Z |
---
license: apache-2.0
---
|
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dev-lockwood-heart-testing/heart_gradio_test
|
dev-lockwood-heart-testing
| 2023-12-15T17:06:06Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:02:45Z |
# adversarial-robustness-toolbox-jatic
Welcome to the Adversarial Robustness Toolbox JATIC Extension repository!
The core Adversarial Robustness Toolbox repository can be found [here](https://github.com/Trusted-AI/adversarial-robustness-toolbox).
## Getting Started
#### Create Virtual Environment & Install Package Dependencies
```bash
$ conda create --name art-jatic-env --file conda-{Insert Your OS}-64.lock
$ conda activate art-jatic-env
$ poetry install
```
## Merge Requests
Please see `.gitlab/marge_request_templates/art-jatic.md` for more information on how to create merge request for this repository.
## Developers & Maintainers
- Jae Ro [([email protected])](mailto:[email protected])
- Mark Baker [([email protected])](mailto:[email protected])
- Adam Lockwood [([email protected])](mailto:[email protected])
- Kieran Fraser [([email protected])](mailto:[email protected])
- Jackson Lee [([email protected])](mailto:[email protected])
|
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di-ai/qkzrd
|
di-ai
| 2023-12-15T17:04:24Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:04:24Z |
Entry not found
|
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di-ai/rcswj
|
di-ai
| 2023-12-15T17:05:03Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:05:03Z |
Entry not found
|
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di-ai/snpwb
|
di-ai
| 2023-12-15T17:05:58Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:05:58Z |
Entry not found
|
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di-ai/gkogq
|
di-ai
| 2023-12-15T17:06:58Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:06:58Z |
Entry not found
|
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di-ai/tgtdn
|
di-ai
| 2023-12-15T17:07:43Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:07:43Z |
Entry not found
|
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tkcho/cp-commerce-clf-kr-sku-brand-f6973148811e137f4ae42b00accaa747
|
tkcho
| 2023-12-15T17:09:37Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:09:37Z |
Entry not found
|
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Karthik001291546/wdp
|
Karthik001291546
| 2023-12-15T21:31:25Z | 0 | 0 | null |
[
"joblib",
"region:us"
] | null | 2023-12-15T17:10:25Z |
Entry not found
|
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vtiyyal1/covid3-mistral-dpo-gptq
|
vtiyyal1
| 2023-12-15T19:29:03Z | 0 | 0 | null |
[
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:TheBloke/OpenHermes-2-Mistral-7B-GPTQ",
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T17:10:36Z |
---
license: apache-2.0
base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ
tags:
- generated_from_trainer
model-index:
- name: covid3-mistral-dpo-gptq
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# covid3-mistral-dpo-gptq
This model is a fine-tuned version of [TheBloke/OpenHermes-2-Mistral-7B-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2-Mistral-7B-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2375
- Rewards/chosen: -2.8294
- Rewards/rejected: -1.7077
- Rewards/accuracies: 0.25
- Rewards/margins: -1.1217
- Logps/rejected: -24.0692
- Logps/chosen: -35.7956
- Logits/rejected: -2.8653
- Logits/chosen: -2.8666
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6957 | 0.0 | 10 | 0.6940 | 0.0226 | 0.0252 | 0.375 | -0.0026 | -6.7409 | -7.2761 | -2.8058 | -2.8067 |
| 0.6925 | 0.0 | 20 | 0.6971 | 0.0317 | 0.0422 | 0.3333 | -0.0105 | -6.5702 | -7.1844 | -2.8074 | -2.8082 |
| 0.6876 | 0.01 | 30 | 0.6995 | 0.0202 | 0.0373 | 0.375 | -0.0170 | -6.6197 | -7.2995 | -2.8093 | -2.8102 |
| 0.6961 | 0.01 | 40 | 0.6982 | 0.0054 | 0.0189 | 0.375 | -0.0135 | -6.8034 | -7.4475 | -2.8113 | -2.8122 |
| 0.6863 | 0.01 | 50 | 0.6998 | 0.0019 | 0.0188 | 0.3333 | -0.0169 | -6.8044 | -7.4830 | -2.8121 | -2.8130 |
| 0.6965 | 0.01 | 60 | 0.6977 | 0.0119 | 0.0251 | 0.2917 | -0.0132 | -6.7419 | -7.3829 | -2.8120 | -2.8129 |
| 0.7209 | 0.01 | 70 | 0.6993 | 0.0336 | 0.0497 | 0.3333 | -0.0161 | -6.4949 | -7.1656 | -2.8103 | -2.8112 |
| 0.6988 | 0.01 | 80 | 0.6984 | 0.0294 | 0.0432 | 0.375 | -0.0138 | -6.5605 | -7.2080 | -2.8085 | -2.8094 |
| 0.6913 | 0.01 | 90 | 0.6981 | 0.0216 | 0.0342 | 0.4167 | -0.0126 | -6.6501 | -7.2856 | -2.8084 | -2.8093 |
| 0.6641 | 0.02 | 100 | 0.7030 | 0.0493 | 0.0702 | 0.3333 | -0.0209 | -6.2907 | -7.0088 | -2.8098 | -2.8107 |
| 0.7083 | 0.02 | 110 | 0.7072 | 0.0575 | 0.0870 | 0.3333 | -0.0295 | -6.1225 | -6.9268 | -2.8105 | -2.8114 |
| 0.6307 | 0.02 | 120 | 0.7128 | 0.0727 | 0.1120 | 0.3333 | -0.0393 | -5.8727 | -6.7749 | -2.8105 | -2.8114 |
| 0.7216 | 0.02 | 130 | 0.7158 | 0.0814 | 0.1250 | 0.3333 | -0.0436 | -5.7422 | -6.6879 | -2.8108 | -2.8117 |
| 0.7189 | 0.02 | 140 | 0.7135 | 0.0948 | 0.1343 | 0.3333 | -0.0395 | -5.6489 | -6.5536 | -2.8099 | -2.8108 |
| 0.7177 | 0.03 | 150 | 0.7128 | 0.0954 | 0.1335 | 0.3333 | -0.0381 | -5.6579 | -6.5481 | -2.8100 | -2.8109 |
| 0.639 | 0.03 | 160 | 0.7232 | 0.0823 | 0.1404 | 0.3333 | -0.0581 | -5.5880 | -6.6785 | -2.8135 | -2.8144 |
| 0.7128 | 0.03 | 170 | 0.7361 | 0.0571 | 0.1393 | 0.375 | -0.0822 | -5.5991 | -6.9308 | -2.8165 | -2.8174 |
| 0.709 | 0.03 | 180 | 0.7361 | 0.0690 | 0.1519 | 0.375 | -0.0829 | -5.4739 | -6.8120 | -2.8159 | -2.8168 |
| 0.6167 | 0.03 | 190 | 0.7483 | 0.0424 | 0.1461 | 0.375 | -0.1038 | -5.5311 | -7.0782 | -2.8180 | -2.8189 |
| 0.7521 | 0.03 | 200 | 0.7589 | 0.0180 | 0.1360 | 0.3333 | -0.1180 | -5.6325 | -7.3223 | -2.8199 | -2.8209 |
| 0.6204 | 0.04 | 210 | 0.7726 | -0.0220 | 0.1130 | 0.375 | -0.1350 | -5.8622 | -7.7214 | -2.8217 | -2.8227 |
| 0.6578 | 0.04 | 220 | 0.7839 | -0.0525 | 0.0994 | 0.3333 | -0.1520 | -5.9980 | -8.0273 | -2.8232 | -2.8242 |
| 0.7633 | 0.04 | 230 | 0.7868 | -0.0613 | 0.0902 | 0.375 | -0.1516 | -6.0903 | -8.1152 | -2.8235 | -2.8245 |
| 0.7391 | 0.04 | 240 | 0.7917 | -0.0742 | 0.0850 | 0.375 | -0.1592 | -6.1429 | -8.2441 | -2.8246 | -2.8256 |
| 0.6759 | 0.04 | 250 | 0.8023 | -0.1101 | 0.0656 | 0.3333 | -0.1757 | -6.3368 | -8.6031 | -2.8262 | -2.8272 |
| 0.6768 | 0.04 | 260 | 0.8107 | -0.1470 | 0.0326 | 0.375 | -0.1796 | -6.6662 | -8.9720 | -2.8264 | -2.8274 |
| 0.5398 | 0.04 | 270 | 0.8411 | -0.2390 | -0.0341 | 0.375 | -0.2049 | -7.3331 | -9.8918 | -2.8279 | -2.8289 |
| 0.5617 | 0.05 | 280 | 0.8797 | -0.3532 | -0.1075 | 0.375 | -0.2457 | -8.0674 | -11.0340 | -2.8306 | -2.8317 |
| 0.7585 | 0.05 | 290 | 0.9009 | -0.4183 | -0.1540 | 0.375 | -0.2642 | -8.5328 | -11.6845 | -2.8318 | -2.8329 |
| 0.4971 | 0.05 | 300 | 0.9602 | -0.5793 | -0.2520 | 0.375 | -0.3274 | -9.5121 | -13.2952 | -2.8362 | -2.8373 |
| 0.5759 | 0.05 | 310 | 1.0568 | -0.8155 | -0.3982 | 0.375 | -0.4173 | -10.9749 | -15.6568 | -2.8426 | -2.8437 |
| 0.451 | 0.05 | 320 | 1.1605 | -1.0527 | -0.5383 | 0.375 | -0.5144 | -12.3754 | -18.0287 | -2.8482 | -2.8493 |
| 1.4199 | 0.06 | 330 | 1.1756 | -1.1393 | -0.6287 | 0.375 | -0.5106 | -13.2791 | -18.8948 | -2.8505 | -2.8516 |
| 0.6853 | 0.06 | 340 | 1.1875 | -1.1840 | -0.6936 | 0.375 | -0.4904 | -13.9281 | -19.3416 | -2.8530 | -2.8541 |
| 0.3956 | 0.06 | 350 | 1.2550 | -1.2944 | -0.7654 | 0.375 | -0.5291 | -14.6460 | -20.4463 | -2.8568 | -2.8579 |
| 0.8692 | 0.06 | 360 | 1.3093 | -1.4107 | -0.8644 | 0.375 | -0.5463 | -15.6363 | -21.6084 | -2.8602 | -2.8613 |
| 1.4214 | 0.06 | 370 | 1.2759 | -1.3853 | -0.8782 | 0.375 | -0.5071 | -15.7746 | -21.3549 | -2.8579 | -2.8590 |
| 0.6163 | 0.06 | 380 | 1.3124 | -1.4537 | -0.9274 | 0.375 | -0.5263 | -16.2665 | -22.0389 | -2.8580 | -2.8591 |
| 0.586 | 0.07 | 390 | 1.4060 | -1.6073 | -1.0263 | 0.375 | -0.5810 | -17.2554 | -23.5750 | -2.8594 | -2.8605 |
| 1.7565 | 0.07 | 400 | 1.3869 | -1.5469 | -0.9534 | 0.375 | -0.5936 | -16.5259 | -22.9709 | -2.8611 | -2.8623 |
| 0.749 | 0.07 | 410 | 1.4037 | -1.5658 | -0.9400 | 0.375 | -0.6258 | -16.3927 | -23.1602 | -2.8615 | -2.8626 |
| 0.7682 | 0.07 | 420 | 1.4444 | -1.6154 | -0.9575 | 0.375 | -0.6578 | -16.5678 | -23.6556 | -2.8618 | -2.8630 |
| 0.5276 | 0.07 | 430 | 1.5646 | -1.7833 | -1.0365 | 0.375 | -0.7467 | -17.3576 | -25.3345 | -2.8645 | -2.8658 |
| 1.2132 | 0.07 | 440 | 1.6229 | -1.8510 | -1.0641 | 0.375 | -0.7869 | -17.6336 | -26.0119 | -2.8657 | -2.8670 |
| 1.0323 | 0.07 | 450 | 1.6468 | -1.8672 | -1.0528 | 0.3333 | -0.8143 | -17.5208 | -26.1736 | -2.8655 | -2.8668 |
| 1.1453 | 0.08 | 460 | 1.6741 | -1.8759 | -1.0266 | 0.3333 | -0.8494 | -17.2580 | -26.2613 | -2.8659 | -2.8672 |
| 1.526 | 0.08 | 470 | 1.6465 | -1.8347 | -1.0076 | 0.3333 | -0.8271 | -17.0681 | -25.8488 | -2.8671 | -2.8684 |
| 1.1323 | 0.08 | 480 | 1.5543 | -1.7064 | -0.9557 | 0.3333 | -0.7507 | -16.5494 | -24.5655 | -2.8682 | -2.8694 |
| 1.0389 | 0.08 | 490 | 1.5824 | -1.7717 | -1.0002 | 0.3333 | -0.7715 | -16.9945 | -25.2190 | -2.8694 | -2.8706 |
| 0.8626 | 0.08 | 500 | 1.6038 | -1.8376 | -1.0545 | 0.3333 | -0.7831 | -17.5374 | -25.8781 | -2.8693 | -2.8706 |
| 0.8392 | 0.09 | 510 | 1.6952 | -1.9873 | -1.1387 | 0.3333 | -0.8486 | -18.3790 | -27.3744 | -2.8697 | -2.8710 |
| 0.6528 | 0.09 | 520 | 1.7895 | -2.1144 | -1.1842 | 0.25 | -0.9302 | -18.8344 | -28.6457 | -2.8693 | -2.8707 |
| 1.3843 | 0.09 | 530 | 1.8088 | -2.1501 | -1.2043 | 0.25 | -0.9458 | -19.0354 | -29.0030 | -2.8696 | -2.8710 |
| 1.296 | 0.09 | 540 | 1.7833 | -2.1309 | -1.2130 | 0.25 | -0.9178 | -19.1228 | -28.8106 | -2.8691 | -2.8705 |
| 0.7343 | 0.09 | 550 | 1.8244 | -2.1833 | -1.2404 | 0.25 | -0.9428 | -19.3968 | -29.3344 | -2.8676 | -2.8689 |
| 1.089 | 0.09 | 560 | 1.8288 | -2.1789 | -1.2313 | 0.25 | -0.9476 | -19.3059 | -29.2912 | -2.8690 | -2.8704 |
| 0.8322 | 0.1 | 570 | 1.9009 | -2.2715 | -1.2811 | 0.25 | -0.9903 | -19.8038 | -30.2165 | -2.8697 | -2.8711 |
| 0.8684 | 0.1 | 580 | 1.9310 | -2.3144 | -1.3151 | 0.25 | -0.9993 | -20.1433 | -30.6454 | -2.8722 | -2.8736 |
| 0.9827 | 0.1 | 590 | 1.9558 | -2.3309 | -1.3222 | 0.25 | -1.0087 | -20.2145 | -30.8112 | -2.8740 | -2.8754 |
| 0.5176 | 0.1 | 600 | 1.9731 | -2.3665 | -1.3574 | 0.25 | -1.0091 | -20.5666 | -31.1672 | -2.8754 | -2.8768 |
| 1.0789 | 0.1 | 610 | 2.0276 | -2.4550 | -1.4152 | 0.25 | -1.0398 | -21.1444 | -32.0516 | -2.8756 | -2.8769 |
| 0.8444 | 0.1 | 620 | 2.1331 | -2.6253 | -1.5121 | 0.25 | -1.1132 | -22.1132 | -33.7550 | -2.8726 | -2.8739 |
| 1.6609 | 0.1 | 630 | 2.1160 | -2.6511 | -1.5573 | 0.25 | -1.0938 | -22.5657 | -34.0127 | -2.8740 | -2.8753 |
| 1.3086 | 0.11 | 640 | 2.0791 | -2.6721 | -1.6152 | 0.25 | -1.0569 | -23.1446 | -34.2231 | -2.8749 | -2.8762 |
| 1.0659 | 0.11 | 650 | 2.0520 | -2.6575 | -1.6184 | 0.25 | -1.0391 | -23.1760 | -34.0763 | -2.8766 | -2.8778 |
| 1.3081 | 0.11 | 660 | 2.0481 | -2.6650 | -1.6332 | 0.25 | -1.0318 | -23.3247 | -34.1520 | -2.8756 | -2.8769 |
| 0.769 | 0.11 | 670 | 2.0971 | -2.7165 | -1.6666 | 0.25 | -1.0500 | -23.6581 | -34.6672 | -2.8745 | -2.8758 |
| 1.1385 | 0.11 | 680 | 2.1554 | -2.7771 | -1.7021 | 0.25 | -1.0750 | -24.0137 | -35.2731 | -2.8735 | -2.8748 |
| 1.0306 | 0.12 | 690 | 2.2076 | -2.8501 | -1.7587 | 0.25 | -1.0914 | -24.5793 | -36.0025 | -2.8714 | -2.8727 |
| 1.3893 | 0.12 | 700 | 2.2299 | -2.8955 | -1.7944 | 0.25 | -1.1010 | -24.9367 | -36.4564 | -2.8682 | -2.8695 |
| 2.2234 | 0.12 | 710 | 2.2237 | -2.9162 | -1.8126 | 0.25 | -1.1036 | -25.1184 | -36.6639 | -2.8654 | -2.8667 |
| 0.4678 | 0.12 | 720 | 2.2379 | -2.9096 | -1.7873 | 0.25 | -1.1223 | -24.8652 | -36.5974 | -2.8658 | -2.8671 |
| 0.8098 | 0.12 | 730 | 2.2768 | -2.9290 | -1.7762 | 0.25 | -1.1529 | -24.7543 | -36.7922 | -2.8652 | -2.8665 |
| 1.8821 | 0.12 | 740 | 2.2740 | -2.9198 | -1.7623 | 0.25 | -1.1574 | -24.6159 | -36.6994 | -2.8641 | -2.8654 |
| 1.095 | 0.12 | 750 | 2.2689 | -2.8862 | -1.7174 | 0.25 | -1.1688 | -24.1662 | -36.3637 | -2.8647 | -2.8660 |
| 1.7464 | 0.13 | 760 | 2.2488 | -2.8828 | -1.7320 | 0.25 | -1.1508 | -24.3128 | -36.3297 | -2.8640 | -2.8653 |
| 0.9967 | 0.13 | 770 | 2.2235 | -2.8783 | -1.7502 | 0.25 | -1.1281 | -24.4945 | -36.2849 | -2.8622 | -2.8634 |
| 0.7823 | 0.13 | 780 | 2.2370 | -2.9074 | -1.7744 | 0.25 | -1.1330 | -24.7361 | -36.5759 | -2.8593 | -2.8606 |
| 1.3903 | 0.13 | 790 | 2.2755 | -2.9143 | -1.7485 | 0.25 | -1.1658 | -24.4774 | -36.6450 | -2.8587 | -2.8600 |
| 2.0372 | 0.13 | 800 | 2.2250 | -2.7892 | -1.6505 | 0.25 | -1.1387 | -23.4972 | -35.3939 | -2.8629 | -2.8642 |
| 0.7111 | 0.14 | 810 | 2.2409 | -2.7911 | -1.6348 | 0.25 | -1.1562 | -23.3407 | -35.4124 | -2.8642 | -2.8654 |
| 0.8446 | 0.14 | 820 | 2.2740 | -2.8395 | -1.6646 | 0.25 | -1.1749 | -23.6383 | -35.8968 | -2.8638 | -2.8651 |
| 1.2303 | 0.14 | 830 | 2.2812 | -2.8540 | -1.6787 | 0.25 | -1.1752 | -23.7798 | -36.0417 | -2.8648 | -2.8661 |
| 0.5053 | 0.14 | 840 | 2.2834 | -2.8740 | -1.7065 | 0.25 | -1.1675 | -24.0571 | -36.2418 | -2.8640 | -2.8653 |
| 0.5767 | 0.14 | 850 | 2.3105 | -2.9262 | -1.7448 | 0.25 | -1.1814 | -24.4399 | -36.7635 | -2.8618 | -2.8631 |
| 1.7435 | 0.14 | 860 | 2.3174 | -2.9360 | -1.7519 | 0.25 | -1.1841 | -24.5119 | -36.8619 | -2.8627 | -2.8639 |
| 1.6134 | 0.14 | 870 | 2.3028 | -2.9288 | -1.7659 | 0.25 | -1.1629 | -24.6517 | -36.7902 | -2.8635 | -2.8647 |
| 1.747 | 0.15 | 880 | 2.2686 | -2.8780 | -1.7398 | 0.25 | -1.1382 | -24.3902 | -36.2816 | -2.8658 | -2.8671 |
| 1.3341 | 0.15 | 890 | 2.2555 | -2.8559 | -1.7244 | 0.25 | -1.1315 | -24.2361 | -36.0610 | -2.8673 | -2.8686 |
| 1.884 | 0.15 | 900 | 2.2349 | -2.8291 | -1.7129 | 0.25 | -1.1162 | -24.1211 | -35.7924 | -2.8677 | -2.8689 |
| 0.5031 | 0.15 | 910 | 2.2361 | -2.8327 | -1.7156 | 0.25 | -1.1171 | -24.1479 | -35.8284 | -2.8671 | -2.8684 |
| 0.7273 | 0.15 | 920 | 2.2545 | -2.8595 | -1.7291 | 0.25 | -1.1304 | -24.2834 | -36.0963 | -2.8665 | -2.8678 |
| 1.2208 | 0.15 | 930 | 2.2655 | -2.8756 | -1.7364 | 0.25 | -1.1393 | -24.3561 | -36.2580 | -2.8656 | -2.8669 |
| 0.6928 | 0.16 | 940 | 2.2697 | -2.8817 | -1.7405 | 0.25 | -1.1412 | -24.3971 | -36.3184 | -2.8652 | -2.8665 |
| 2.2099 | 0.16 | 950 | 2.2581 | -2.8642 | -1.7302 | 0.25 | -1.1340 | -24.2945 | -36.1442 | -2.8656 | -2.8668 |
| 1.6883 | 0.16 | 960 | 2.2544 | -2.8575 | -1.7258 | 0.25 | -1.1318 | -24.2503 | -36.0772 | -2.8656 | -2.8668 |
| 1.9968 | 0.16 | 970 | 2.2455 | -2.8405 | -1.7135 | 0.25 | -1.1271 | -24.1270 | -35.9072 | -2.8657 | -2.8670 |
| 2.1044 | 0.16 | 980 | 2.2400 | -2.8308 | -1.7064 | 0.25 | -1.1243 | -24.0569 | -35.8097 | -2.8656 | -2.8668 |
| 0.7207 | 0.17 | 990 | 2.2376 | -2.8286 | -1.7067 | 0.25 | -1.1218 | -24.0597 | -35.7875 | -2.8654 | -2.8667 |
| 1.1388 | 0.17 | 1000 | 2.2375 | -2.8294 | -1.7077 | 0.25 | -1.1217 | -24.0692 | -35.7956 | -2.8653 | -2.8666 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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G-ML-Hyly/stg-cli7b-t4.ca.mips.inter.concat.cln-b4s1e1-20231122-1507-merged
|
G-ML-Hyly
| 2023-12-15T17:11:38Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:11:38Z |
Entry not found
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dcs83/Llama-2-7b-hf-subind-segment-testing
|
dcs83
| 2023-12-15T17:11:55Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:11:55Z |
Entry not found
|
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dcs83/Llama-2-7b-hf-subind-segment-testing-2
|
dcs83
| 2023-12-15T17:12:15Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:12:15Z |
Entry not found
|
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wdgtl/Atherosclerotic_Lesion_Segmentation
|
wdgtl
| 2023-12-15T17:12:33Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:12:33Z |
Entry not found
|
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] |
ange0102/MLOPS_drfit_detector
|
ange0102
| 2023-12-15T17:19:27Z | 0 | 0 | null |
[
"license:mit",
"region:us"
] | null | 2023-12-15T17:12:47Z |
---
license: mit
---
|
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davisudo2000/MassacreGF
|
davisudo2000
| 2023-12-15T17:13:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:12:51Z |
Entry not found
|
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w601sxs/stock-tweets-tokenizer
|
w601sxs
| 2023-12-15T17:14:08Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:14:07Z |
Entry not found
|
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] |
stvhuang/rcr-run-b9bhsr7n-62291-master-0_20231213T152412-ep02
|
stvhuang
| 2023-12-15T17:15:28Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"deberta-v2",
"feature-extraction",
"endpoints_compatible",
"region:us"
] |
feature-extraction
| 2023-12-15T17:14:17Z |
Entry not found
|
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] |
niltheory/ExistenceTypesAnalysis
|
niltheory
| 2023-12-17T17:14:01Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"bert",
"text-classification",
"creative writing",
"original ip",
"en",
"dataset:niltheory/ExistenceTypes",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:15:00Z |
---
datasets:
- niltheory/ExistenceTypes
language:
- en
license: cc-by-sa-4.0
library_name: transformers
tags:
- creative writing
- original ip
---
# Existence Analysis Model (EAM)
**Created for**: Compendium Terminum, IP
**Base Model**: `bert-large-cased-whole-word-masking`
## Iterative Development
### Iteration #1:
- **Initial Model**: Utilized `distilBert` for foundational training.
- **Dataset Size**: 96 entries.
- **Outcome**: Established baseline for accuracy metrics.
### Iteration #2:
- **Model Upgrade**: Transitioned to `bert-base-uncased` from `distilbert-base-uncased`.
- **Dataset Expansion**: Increased from 96 to 296 entries.
- **Performance**: Improved accuracy scores; identified edge cases for refinement.
### Iteration #3:
- **Model Upgrade**: Transitioned to `bert-large-cased-whole-word-masking` from `bert-base-uncased`.
- **Advancements**: Enhanced contextual sensitivity and accuracy.
- **Results**: Demonstrated more nuanced understanding and sensitivity in predictions.
## Observations
- Each iteration has contributed to the model's evolving sophistication, leading to improved interpretive performance and accuracy.
- Continuous evaluation, especially in complex or ambiguous cases, is pivotal for future enhancements.
|
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lliillyy/M87-deblur-MAD-ksize-23-fintune-lr_5e-05-steps_8000
|
lliillyy
| 2023-12-15T17:17:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:17:10Z |
Entry not found
|
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PowerInfer/ReluLLaMA-7B-PowerInfer-GGUF
|
PowerInfer
| 2023-12-16T08:59:05Z | 0 | 0 | null |
[
"gguf",
"en",
"license:llama2",
"region:us"
] | null | 2023-12-15T17:17:54Z |
---
license: llama2
language:
- en
---
# ReluLLaMA-7B-PowerInfer-GGUF
- Original model: [SparseLLM/ReluLLaMA-7B](https://huggingface.co/SparseLLM/ReluLLaMA-7B)
- Converted & distributed by: [PowerInfer](https://huggingface.co/PowerInfer)
This model is the downstream distribution of [SparseLLM/ReluLLaMA-7B](https://huggingface.co/SparseLLM/ReluLLaMA-7B) in PowerInfer GGUF format consisting of the LLM model weights and predictor weights.
|
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] |
Lin25/wav2vec2-large-mms-1b-england-1216-adapter-test
|
Lin25
| 2023-12-15T18:33:12Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2023-12-15T17:19:08Z |
Entry not found
|
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] |
akashsingh/mms-tts-tel-train
|
akashsingh
| 2023-12-15T17:25:54Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"vits",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2023-12-15T17:19:12Z |
---
license: cc-by-4.0
---
|
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] |
Jeevesh8/bt__qqp_ft_only_data_shuff_20
|
Jeevesh8
| 2023-12-15T19:52:55Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:21:29Z |
Entry not found
|
[
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] |
ac0hik/camembert_model
|
ac0hik
| 2023-12-17T17:08:56Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"camembert",
"text-classification",
"generated_from_trainer",
"dataset:tweet_sentiment_multilingual",
"base_model:camembert-base",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:21:45Z |
---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
model-index:
- name: camembert_model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tweet_sentiment_multilingual
type: tweet_sentiment_multilingual
config: french
split: validation
args: french
metrics:
- name: Accuracy
type: accuracy
value: 0.7654320987654321
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# camembert_model
This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the tweet_sentiment_multilingual dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7877
- Accuracy: 0.7654
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 115 | 0.8510 | 0.6265 |
| No log | 2.0 | 230 | 0.7627 | 0.7130 |
| No log | 3.0 | 345 | 0.6966 | 0.7160 |
| No log | 4.0 | 460 | 0.6862 | 0.7438 |
| 0.7126 | 5.0 | 575 | 0.6637 | 0.75 |
| 0.7126 | 6.0 | 690 | 0.7121 | 0.7654 |
| 0.7126 | 7.0 | 805 | 0.7641 | 0.7438 |
| 0.7126 | 8.0 | 920 | 0.7662 | 0.7654 |
| 0.2932 | 9.0 | 1035 | 0.7765 | 0.7747 |
| 0.2932 | 10.0 | 1150 | 0.7877 | 0.7654 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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] |
delayedkarma/marian-finetuned-kde4-en-to-fr-accelerate
|
delayedkarma
| 2023-12-15T20:06:28Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"marian",
"text2text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2023-12-15T17:23:12Z |
---
license: apache-2.0
---
|
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ADISH007/Aws_donut_10k_incremental_1_Epoch_29
|
ADISH007
| 2023-12-15T17:25:17Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"vision-encoder-decoder",
"endpoints_compatible",
"region:us"
] | null | 2023-12-15T17:24:56Z |
Entry not found
|
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ADISH007/Finetuned_Donut_aws_10k_incremental_1_Final_model
|
ADISH007
| 2023-12-15T17:25:37Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"vision-encoder-decoder",
"endpoints_compatible",
"region:us"
] | null | 2023-12-15T17:25:18Z |
Entry not found
|
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0.31015992164611816,
-1.0262157917022705
] |
andresproc/whisper
|
andresproc
| 2023-12-15T17:26:23Z | 0 | 0 |
keras
|
[
"keras",
"text-classification",
"es",
"dataset:gaia-benchmark/GAIA",
"license:apache-2.0",
"region:us"
] |
text-classification
| 2023-12-15T17:25:31Z |
---
license: apache-2.0
datasets:
- gaia-benchmark/GAIA
language:
- es
metrics:
- bleurt
library_name: keras
pipeline_tag: text-classification
---
|
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] |
ppbrown/divine-elegance-unmerge
|
ppbrown
| 2023-12-15T19:33:15Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-15T17:25:49Z |
---
license: openrail
---
Attempt to see if I can make models generate more accurate stuff by default.
This time, playing with divine elegance model.
ComfyUI workflow2 included as json file
the "unmerge2" varient is better IMO
|
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lliillyy/M87-deblur-MAD-ksize-23-finetune-lr_5e-05-steps_8000
|
lliillyy
| 2023-12-15T21:51:06Z | 0 | 0 |
diffusers
|
[
"diffusers",
"safetensors",
"diffusers:StableDiffusionInstructPix2PixPipeline",
"region:us"
] | null | 2023-12-15T17:27:41Z |
Entry not found
|
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bluemoonai/sdxl-models
|
bluemoonai
| 2023-12-16T18:01:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:29:59Z |
Entry not found
|
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] |
Jeevesh8/bt_re__qqp_ft_1
|
Jeevesh8
| 2023-12-15T19:56:13Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:36:37Z |
Entry not found
|
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Jeevesh8/bt_re__qqp_ft_2
|
Jeevesh8
| 2023-12-15T19:55:37Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:36:37Z |
Entry not found
|
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] |
Jeevesh8/bt_re__qqp_ft_0
|
Jeevesh8
| 2023-12-15T19:48:11Z | 0 | 0 |
transformers
|
[
"transformers",
"jax",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:36:37Z |
Entry not found
|
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platzi/clasificacion-DBpedia-edwar-xd
|
platzi
| 2023-12-15T17:52:02Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:36:51Z |
Entry not found
|
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di-ai/mpoqf
|
di-ai
| 2023-12-15T17:37:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:37:53Z |
Entry not found
|
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di-ai/ttrrj
|
di-ai
| 2023-12-15T17:38:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:38:53Z |
Entry not found
|
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pjc2178/test_trainer
|
pjc2178
| 2023-12-15T17:39:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:39:20Z |
Entry not found
|
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di-ai/dyfyt
|
di-ai
| 2023-12-15T17:39:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:39:45Z |
Entry not found
|
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di-ai/kzynq
|
di-ai
| 2023-12-15T17:40:39Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:40:39Z |
Entry not found
|
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] |
pjc2178/legal-bert-SCAL-predict-v1
|
pjc2178
| 2023-12-15T17:45:49Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:41:11Z |
Entry not found
|
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di-ai/pitzc
|
di-ai
| 2023-12-15T17:41:27Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:41:26Z |
Entry not found
|
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NazarShved/NazarShved
|
NazarShved
| 2023-12-15T17:41:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:41:59Z |
Entry not found
|
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Vermiculos/james
|
Vermiculos
| 2023-12-15T17:48:42Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-15T17:44:52Z |
---
license: openrail
---
|
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Ash-8825/Tweet_Generator
|
Ash-8825
| 2023-12-15T17:46:03Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:46:03Z |
Entry not found
|
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] |
NeuroDonu/2urbina
|
NeuroDonu
| 2023-12-15T17:54:22Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2023-12-15T17:50:00Z |
---
license: apache-2.0
---
|
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] |
Vermiculos/masterjames
|
Vermiculos
| 2023-12-15T17:57:01Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-15T17:52:57Z |
---
license: openrail
---
|
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Prezily/distilbert-twitter-yelp
|
Prezily
| 2023-12-15T17:53:23Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:53:23Z |
Entry not found
|
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] |
pjc2178/legal-bert-SCAL-predict-f1-max
|
pjc2178
| 2023-12-15T22:40:06Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-15T17:53:42Z |
Entry not found
|
[
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jysh1023/saved_results
|
jysh1023
| 2023-12-15T17:54:49Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:54:49Z |
Entry not found
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npvinHnivqn/phi-2-finetuned
|
npvinHnivqn
| 2023-12-15T17:58:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-15T17:58:57Z |
Invalid username or password.
|
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