---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-1
  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. -->

# distilbert-base-uncased__sst2__train-32-1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6492
- Accuracy: 0.6551

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7106        | 1.0   | 13   | 0.6850          | 0.6154   |
| 0.631         | 2.0   | 26   | 0.6632          | 0.6923   |
| 0.5643        | 3.0   | 39   | 0.6247          | 0.7692   |
| 0.3992        | 4.0   | 52   | 0.5948          | 0.7692   |
| 0.1928        | 5.0   | 65   | 0.5803          | 0.7692   |
| 0.0821        | 6.0   | 78   | 0.6404          | 0.6923   |
| 0.0294        | 7.0   | 91   | 0.7387          | 0.6923   |
| 0.0141        | 8.0   | 104  | 0.8270          | 0.6923   |
| 0.0082        | 9.0   | 117  | 0.8496          | 0.6923   |
| 0.0064        | 10.0  | 130  | 0.8679          | 0.6923   |
| 0.005         | 11.0  | 143  | 0.8914          | 0.6923   |
| 0.0036        | 12.0  | 156  | 0.9278          | 0.6923   |
| 0.0031        | 13.0  | 169  | 0.9552          | 0.6923   |
| 0.0029        | 14.0  | 182  | 0.9745          | 0.6923   |
| 0.0028        | 15.0  | 195  | 0.9785          | 0.6923   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-9
  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. -->

# distilbert-base-uncased__hate_speech_offensive__train-8-9

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0959
- Accuracy: 0.093

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1068        | 1.0   | 5    | 1.1545          | 0.0      |
| 1.0494        | 2.0   | 10   | 1.1971          | 0.0      |
| 1.0612        | 3.0   | 15   | 1.2164          | 0.0      |
| 0.9517        | 4.0   | 20   | 1.2545          | 0.0      |
| 0.8874        | 5.0   | 25   | 1.2699          | 0.0      |
| 0.8598        | 6.0   | 30   | 1.2835          | 0.0      |
| 0.7006        | 7.0   | 35   | 1.3139          | 0.0      |
| 0.5969        | 8.0   | 40   | 1.3116          | 0.2      |
| 0.4769        | 9.0   | 45   | 1.3124          | 0.4      |
| 0.4352        | 10.0  | 50   | 1.3541          | 0.4      |
| 0.3231        | 11.0  | 55   | 1.3919          | 0.4      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-16-3
  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. -->

# distilbert-base-uncased__sst2__train-16-3

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7887
- Accuracy: 0.6458

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6928        | 1.0   | 7    | 0.6973          | 0.4286   |
| 0.675         | 2.0   | 14   | 0.7001          | 0.4286   |
| 0.6513        | 3.0   | 21   | 0.6959          | 0.4286   |
| 0.5702        | 4.0   | 28   | 0.6993          | 0.4286   |
| 0.5389        | 5.0   | 35   | 0.6020          | 0.7143   |
| 0.3386        | 6.0   | 42   | 0.5326          | 0.5714   |
| 0.2596        | 7.0   | 49   | 0.4943          | 0.7143   |
| 0.1633        | 8.0   | 56   | 0.3589          | 0.8571   |
| 0.1086        | 9.0   | 63   | 0.2924          | 0.8571   |
| 0.0641        | 10.0  | 70   | 0.2687          | 0.8571   |
| 0.0409        | 11.0  | 77   | 0.2202          | 0.8571   |
| 0.0181        | 12.0  | 84   | 0.2445          | 0.8571   |
| 0.0141        | 13.0  | 91   | 0.2885          | 0.8571   |
| 0.0108        | 14.0  | 98   | 0.3069          | 0.8571   |
| 0.009         | 15.0  | 105  | 0.3006          | 0.8571   |
| 0.0084        | 16.0  | 112  | 0.2834          | 0.8571   |
| 0.0088        | 17.0  | 119  | 0.2736          | 0.8571   |
| 0.0062        | 18.0  | 126  | 0.2579          | 0.8571   |
| 0.0058        | 19.0  | 133  | 0.2609          | 0.8571   |
| 0.0057        | 20.0  | 140  | 0.2563          | 0.8571   |
| 0.0049        | 21.0  | 147  | 0.2582          | 0.8571   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-16-2
  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. -->

# distilbert-base-uncased__sst2__train-16-2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6748
- Accuracy: 0.6315

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7043        | 1.0   | 7    | 0.7054          | 0.2857   |
| 0.6711        | 2.0   | 14   | 0.7208          | 0.2857   |
| 0.6311        | 3.0   | 21   | 0.7365          | 0.2857   |
| 0.551         | 4.0   | 28   | 0.7657          | 0.5714   |
| 0.5599        | 5.0   | 35   | 0.6915          | 0.5714   |
| 0.3167        | 6.0   | 42   | 0.7134          | 0.5714   |
| 0.2489        | 7.0   | 49   | 0.7892          | 0.5714   |
| 0.1985        | 8.0   | 56   | 0.6756          | 0.7143   |
| 0.0864        | 9.0   | 63   | 0.8059          | 0.5714   |
| 0.0903        | 10.0  | 70   | 0.8165          | 0.7143   |
| 0.0429        | 11.0  | 77   | 0.7947          | 0.7143   |
| 0.0186        | 12.0  | 84   | 0.8570          | 0.7143   |
| 0.0146        | 13.0  | 91   | 0.9346          | 0.7143   |
| 0.011         | 14.0  | 98   | 0.9804          | 0.7143   |
| 0.0098        | 15.0  | 105  | 1.0136          | 0.7143   |
| 0.0086        | 16.0  | 112  | 1.0424          | 0.7143   |
| 0.0089        | 17.0  | 119  | 1.0736          | 0.7143   |
| 0.0068        | 18.0  | 126  | 1.0808          | 0.7143   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-5
  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. -->

# distilbert-base-uncased__subj__train-8-5

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6927
- Accuracy: 0.506

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7102        | 1.0   | 3    | 0.6790          | 0.75     |
| 0.6693        | 2.0   | 6    | 0.6831          | 0.75     |
| 0.6438        | 3.0   | 9    | 0.6876          | 0.75     |
| 0.6047        | 4.0   | 12   | 0.6970          | 0.75     |
| 0.547         | 5.0   | 15   | 0.7065          | 0.75     |
| 0.4885        | 6.0   | 18   | 0.7114          | 0.75     |
| 0.4601        | 7.0   | 21   | 0.7147          | 0.5      |
| 0.4017        | 8.0   | 24   | 0.7178          | 0.5      |
| 0.3474        | 9.0   | 27   | 0.7145          | 0.5      |
| 0.2624        | 10.0  | 30   | 0.7153          | 0.5      |
| 0.2175        | 11.0  | 33   | 0.7158          | 0.5      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-1
  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. -->

# distilbert-base-uncased__subj__train-8-1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5488
- Accuracy: 0.791

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.703         | 1.0   | 3    | 0.6906          | 0.5      |
| 0.666         | 2.0   | 6    | 0.6945          | 0.25     |
| 0.63          | 3.0   | 9    | 0.6885          | 0.5      |
| 0.588         | 4.0   | 12   | 0.6888          | 0.25     |
| 0.5181        | 5.0   | 15   | 0.6899          | 0.25     |
| 0.4508        | 6.0   | 18   | 0.6770          | 0.5      |
| 0.4025        | 7.0   | 21   | 0.6579          | 0.5      |
| 0.3361        | 8.0   | 24   | 0.6392          | 0.5      |
| 0.2919        | 9.0   | 27   | 0.6113          | 0.5      |
| 0.2151        | 10.0  | 30   | 0.5774          | 0.75     |
| 0.1728        | 11.0  | 33   | 0.5248          | 0.75     |
| 0.1313        | 12.0  | 36   | 0.4824          | 0.75     |
| 0.1046        | 13.0  | 39   | 0.4456          | 0.75     |
| 0.0858        | 14.0  | 42   | 0.4076          | 0.75     |
| 0.0679        | 15.0  | 45   | 0.3755          | 0.75     |
| 0.0485        | 16.0  | 48   | 0.3422          | 0.75     |
| 0.0416        | 17.0  | 51   | 0.3055          | 0.75     |
| 0.0358        | 18.0  | 54   | 0.2731          | 1.0      |
| 0.0277        | 19.0  | 57   | 0.2443          | 1.0      |
| 0.0234        | 20.0  | 60   | 0.2187          | 1.0      |
| 0.0223        | 21.0  | 63   | 0.1960          | 1.0      |
| 0.0187        | 22.0  | 66   | 0.1762          | 1.0      |
| 0.017         | 23.0  | 69   | 0.1629          | 1.0      |
| 0.0154        | 24.0  | 72   | 0.1543          | 1.0      |
| 0.0164        | 25.0  | 75   | 0.1476          | 1.0      |
| 0.0131        | 26.0  | 78   | 0.1423          | 1.0      |
| 0.0139        | 27.0  | 81   | 0.1387          | 1.0      |
| 0.0107        | 28.0  | 84   | 0.1360          | 1.0      |
| 0.0108        | 29.0  | 87   | 0.1331          | 1.0      |
| 0.0105        | 30.0  | 90   | 0.1308          | 1.0      |
| 0.0106        | 31.0  | 93   | 0.1276          | 1.0      |
| 0.0104        | 32.0  | 96   | 0.1267          | 1.0      |
| 0.0095        | 33.0  | 99   | 0.1255          | 1.0      |
| 0.0076        | 34.0  | 102  | 0.1243          | 1.0      |
| 0.0094        | 35.0  | 105  | 0.1235          | 1.0      |
| 0.0103        | 36.0  | 108  | 0.1228          | 1.0      |
| 0.0086        | 37.0  | 111  | 0.1231          | 1.0      |
| 0.0094        | 38.0  | 114  | 0.1236          | 1.0      |
| 0.0074        | 39.0  | 117  | 0.1240          | 1.0      |
| 0.0085        | 40.0  | 120  | 0.1246          | 1.0      |
| 0.0079        | 41.0  | 123  | 0.1253          | 1.0      |
| 0.0088        | 42.0  | 126  | 0.1248          | 1.0      |
| 0.0082        | 43.0  | 129  | 0.1244          | 1.0      |
| 0.0082        | 44.0  | 132  | 0.1234          | 1.0      |
| 0.0082        | 45.0  | 135  | 0.1223          | 1.0      |
| 0.0071        | 46.0  | 138  | 0.1212          | 1.0      |
| 0.0073        | 47.0  | 141  | 0.1208          | 1.0      |
| 0.0081        | 48.0  | 144  | 0.1205          | 1.0      |
| 0.0067        | 49.0  | 147  | 0.1202          | 1.0      |
| 0.0077        | 50.0  | 150  | 0.1202          | 1.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-3
  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. -->

# distilbert-base-uncased__hate_speech_offensive__train-8-3

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9681
- Accuracy: 0.549

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1073        | 1.0   | 5    | 1.1393          | 0.0      |
| 1.0392        | 2.0   | 10   | 1.1729          | 0.0      |
| 1.0302        | 3.0   | 15   | 1.1694          | 0.2      |
| 0.9176        | 4.0   | 20   | 1.1846          | 0.2      |
| 0.8339        | 5.0   | 25   | 1.1663          | 0.2      |
| 0.7533        | 6.0   | 30   | 1.1513          | 0.4      |
| 0.6327        | 7.0   | 35   | 1.1474          | 0.4      |
| 0.4402        | 8.0   | 40   | 1.1385          | 0.4      |
| 0.3752        | 9.0   | 45   | 1.0965          | 0.2      |
| 0.3448        | 10.0  | 50   | 1.0357          | 0.2      |
| 0.2582        | 11.0  | 55   | 1.0438          | 0.2      |
| 0.1903        | 12.0  | 60   | 1.0561          | 0.2      |
| 0.1479        | 13.0  | 65   | 1.0569          | 0.2      |
| 0.1129        | 14.0  | 70   | 1.0455          | 0.2      |
| 0.1071        | 15.0  | 75   | 1.0416          | 0.4      |
| 0.0672        | 16.0  | 80   | 1.1164          | 0.4      |
| 0.0561        | 17.0  | 85   | 1.1846          | 0.6      |
| 0.0463        | 18.0  | 90   | 1.2040          | 0.6      |
| 0.0431        | 19.0  | 95   | 1.2078          | 0.6      |
| 0.0314        | 20.0  | 100  | 1.2368          | 0.6      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-9
  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. -->

# distilbert-base-uncased__sst2__train-8-9

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6925
- Accuracy: 0.5140

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7204        | 1.0   | 3    | 0.7025          | 0.5      |
| 0.6885        | 2.0   | 6    | 0.7145          | 0.5      |
| 0.6662        | 3.0   | 9    | 0.7222          | 0.5      |
| 0.6182        | 4.0   | 12   | 0.7427          | 0.25     |
| 0.5707        | 5.0   | 15   | 0.7773          | 0.25     |
| 0.5247        | 6.0   | 18   | 0.8137          | 0.25     |
| 0.5003        | 7.0   | 21   | 0.8556          | 0.25     |
| 0.4195        | 8.0   | 24   | 0.9089          | 0.5      |
| 0.387         | 9.0   | 27   | 0.9316          | 0.25     |
| 0.2971        | 10.0  | 30   | 0.9558          | 0.25     |
| 0.2581        | 11.0  | 33   | 0.9420          | 0.25     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-4
  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. -->

# distilbert-base-uncased__sst2__train-32-4

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5001
- Accuracy: 0.7650

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7175        | 1.0   | 13   | 0.6822          | 0.5385   |
| 0.6559        | 2.0   | 26   | 0.6533          | 0.6154   |
| 0.6052        | 3.0   | 39   | 0.5762          | 0.7692   |
| 0.4587        | 4.0   | 52   | 0.4477          | 0.8462   |
| 0.2459        | 5.0   | 65   | 0.4288          | 0.7692   |
| 0.1001        | 6.0   | 78   | 0.5219          | 0.7692   |
| 0.0308        | 7.0   | 91   | 0.8540          | 0.7692   |
| 0.014         | 8.0   | 104  | 0.7789          | 0.7692   |
| 0.0083        | 9.0   | 117  | 0.7996          | 0.7692   |
| 0.0064        | 10.0  | 130  | 0.8342          | 0.7692   |
| 0.0049        | 11.0  | 143  | 0.8612          | 0.7692   |
| 0.0036        | 12.0  | 156  | 0.8834          | 0.7692   |
| 0.0032        | 13.0  | 169  | 0.9067          | 0.7692   |
| 0.003         | 14.0  | 182  | 0.9332          | 0.7692   |
| 0.0028        | 15.0  | 195  | 0.9511          | 0.7692   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-4
  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. -->

# distilbert-base-uncased__hate_speech_offensive__train-8-4

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1045
- Accuracy: 0.128

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1115        | 1.0   | 5    | 1.1174          | 0.0      |
| 1.0518        | 2.0   | 10   | 1.1379          | 0.0      |
| 1.0445        | 3.0   | 15   | 1.1287          | 0.0      |
| 0.9306        | 4.0   | 20   | 1.1324          | 0.2      |
| 0.8242        | 5.0   | 25   | 1.1219          | 0.2      |
| 0.7986        | 6.0   | 30   | 1.1369          | 0.4      |
| 0.7369        | 7.0   | 35   | 1.1732          | 0.2      |
| 0.534         | 8.0   | 40   | 1.1828          | 0.6      |
| 0.4285        | 9.0   | 45   | 1.1482          | 0.6      |
| 0.3691        | 10.0  | 50   | 1.1401          | 0.6      |
| 0.3215        | 11.0  | 55   | 1.1286          | 0.6      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-2
  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. -->

# distilbert-base-uncased__subj__train-8-2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3081
- Accuracy: 0.8755

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7146        | 1.0   | 3    | 0.6798          | 0.75     |
| 0.6737        | 2.0   | 6    | 0.6847          | 0.75     |
| 0.6519        | 3.0   | 9    | 0.6783          | 0.75     |
| 0.6105        | 4.0   | 12   | 0.6812          | 0.25     |
| 0.5463        | 5.0   | 15   | 0.6869          | 0.25     |
| 0.4922        | 6.0   | 18   | 0.6837          | 0.5      |
| 0.4543        | 7.0   | 21   | 0.6716          | 0.5      |
| 0.3856        | 8.0   | 24   | 0.6613          | 0.75     |
| 0.3475        | 9.0   | 27   | 0.6282          | 0.75     |
| 0.2717        | 10.0  | 30   | 0.6045          | 0.75     |
| 0.2347        | 11.0  | 33   | 0.5620          | 0.75     |
| 0.1979        | 12.0  | 36   | 0.5234          | 1.0      |
| 0.1535        | 13.0  | 39   | 0.4771          | 1.0      |
| 0.1332        | 14.0  | 42   | 0.4277          | 1.0      |
| 0.1041        | 15.0  | 45   | 0.3785          | 1.0      |
| 0.082         | 16.0  | 48   | 0.3318          | 1.0      |
| 0.0672        | 17.0  | 51   | 0.2885          | 1.0      |
| 0.0538        | 18.0  | 54   | 0.2568          | 1.0      |
| 0.0412        | 19.0  | 57   | 0.2356          | 1.0      |
| 0.0361        | 20.0  | 60   | 0.2217          | 1.0      |
| 0.0303        | 21.0  | 63   | 0.2125          | 1.0      |
| 0.0268        | 22.0  | 66   | 0.2060          | 1.0      |
| 0.0229        | 23.0  | 69   | 0.2015          | 1.0      |
| 0.0215        | 24.0  | 72   | 0.1989          | 1.0      |
| 0.0211        | 25.0  | 75   | 0.1969          | 1.0      |
| 0.0172        | 26.0  | 78   | 0.1953          | 1.0      |
| 0.0165        | 27.0  | 81   | 0.1935          | 1.0      |
| 0.0132        | 28.0  | 84   | 0.1923          | 1.0      |
| 0.0146        | 29.0  | 87   | 0.1914          | 1.0      |
| 0.0125        | 30.0  | 90   | 0.1904          | 1.0      |
| 0.0119        | 31.0  | 93   | 0.1897          | 1.0      |
| 0.0122        | 32.0  | 96   | 0.1886          | 1.0      |
| 0.0118        | 33.0  | 99   | 0.1875          | 1.0      |
| 0.0097        | 34.0  | 102  | 0.1866          | 1.0      |
| 0.0111        | 35.0  | 105  | 0.1861          | 1.0      |
| 0.0111        | 36.0  | 108  | 0.1855          | 1.0      |
| 0.0102        | 37.0  | 111  | 0.1851          | 1.0      |
| 0.0109        | 38.0  | 114  | 0.1851          | 1.0      |
| 0.0085        | 39.0  | 117  | 0.1854          | 1.0      |
| 0.0089        | 40.0  | 120  | 0.1855          | 1.0      |
| 0.0092        | 41.0  | 123  | 0.1863          | 1.0      |
| 0.0105        | 42.0  | 126  | 0.1868          | 1.0      |
| 0.0089        | 43.0  | 129  | 0.1874          | 1.0      |
| 0.0091        | 44.0  | 132  | 0.1877          | 1.0      |
| 0.0096        | 45.0  | 135  | 0.1881          | 1.0      |
| 0.0081        | 46.0  | 138  | 0.1881          | 1.0      |
| 0.0086        | 47.0  | 141  | 0.1883          | 1.0      |
| 0.009         | 48.0  | 144  | 0.1884          | 1.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-8
  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. -->

# distilbert-base-uncased__subj__train-8-8

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3160
- Accuracy: 0.8735

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7187        | 1.0   | 3    | 0.6776          | 1.0      |
| 0.684         | 2.0   | 6    | 0.6608          | 1.0      |
| 0.6532        | 3.0   | 9    | 0.6364          | 1.0      |
| 0.5996        | 4.0   | 12   | 0.6119          | 1.0      |
| 0.5242        | 5.0   | 15   | 0.5806          | 1.0      |
| 0.4612        | 6.0   | 18   | 0.5320          | 1.0      |
| 0.4192        | 7.0   | 21   | 0.4714          | 1.0      |
| 0.3274        | 8.0   | 24   | 0.4071          | 1.0      |
| 0.2871        | 9.0   | 27   | 0.3378          | 1.0      |
| 0.2082        | 10.0  | 30   | 0.2822          | 1.0      |
| 0.1692        | 11.0  | 33   | 0.2271          | 1.0      |
| 0.1242        | 12.0  | 36   | 0.1793          | 1.0      |
| 0.0977        | 13.0  | 39   | 0.1417          | 1.0      |
| 0.0776        | 14.0  | 42   | 0.1117          | 1.0      |
| 0.0631        | 15.0  | 45   | 0.0894          | 1.0      |
| 0.0453        | 16.0  | 48   | 0.0733          | 1.0      |
| 0.0399        | 17.0  | 51   | 0.0617          | 1.0      |
| 0.0333        | 18.0  | 54   | 0.0528          | 1.0      |
| 0.0266        | 19.0  | 57   | 0.0454          | 1.0      |
| 0.0234        | 20.0  | 60   | 0.0393          | 1.0      |
| 0.0223        | 21.0  | 63   | 0.0345          | 1.0      |
| 0.0195        | 22.0  | 66   | 0.0309          | 1.0      |
| 0.0161        | 23.0  | 69   | 0.0281          | 1.0      |
| 0.0167        | 24.0  | 72   | 0.0260          | 1.0      |
| 0.0163        | 25.0  | 75   | 0.0242          | 1.0      |
| 0.0134        | 26.0  | 78   | 0.0227          | 1.0      |
| 0.0128        | 27.0  | 81   | 0.0214          | 1.0      |
| 0.0101        | 28.0  | 84   | 0.0204          | 1.0      |
| 0.0109        | 29.0  | 87   | 0.0194          | 1.0      |
| 0.0112        | 30.0  | 90   | 0.0186          | 1.0      |
| 0.0108        | 31.0  | 93   | 0.0179          | 1.0      |
| 0.011         | 32.0  | 96   | 0.0174          | 1.0      |
| 0.0099        | 33.0  | 99   | 0.0169          | 1.0      |
| 0.0083        | 34.0  | 102  | 0.0164          | 1.0      |
| 0.0096        | 35.0  | 105  | 0.0160          | 1.0      |
| 0.01          | 36.0  | 108  | 0.0156          | 1.0      |
| 0.0084        | 37.0  | 111  | 0.0152          | 1.0      |
| 0.0089        | 38.0  | 114  | 0.0149          | 1.0      |
| 0.0073        | 39.0  | 117  | 0.0146          | 1.0      |
| 0.0082        | 40.0  | 120  | 0.0143          | 1.0      |
| 0.008         | 41.0  | 123  | 0.0141          | 1.0      |
| 0.0093        | 42.0  | 126  | 0.0139          | 1.0      |
| 0.0078        | 43.0  | 129  | 0.0138          | 1.0      |
| 0.0086        | 44.0  | 132  | 0.0136          | 1.0      |
| 0.009         | 45.0  | 135  | 0.0135          | 1.0      |
| 0.0072        | 46.0  | 138  | 0.0134          | 1.0      |
| 0.0075        | 47.0  | 141  | 0.0133          | 1.0      |
| 0.0082        | 48.0  | 144  | 0.0133          | 1.0      |
| 0.0068        | 49.0  | 147  | 0.0132          | 1.0      |
| 0.0074        | 50.0  | 150  | 0.0132          | 1.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-2
  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. -->

# distilbert-base-uncased__sst2__train-8-2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.4931

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7081        | 1.0   | 3    | 0.7031          | 0.25     |
| 0.6853        | 2.0   | 6    | 0.7109          | 0.25     |
| 0.6696        | 3.0   | 9    | 0.7211          | 0.25     |
| 0.6174        | 4.0   | 12   | 0.7407          | 0.25     |
| 0.5717        | 5.0   | 15   | 0.7625          | 0.25     |
| 0.5096        | 6.0   | 18   | 0.7732          | 0.25     |
| 0.488         | 7.0   | 21   | 0.7798          | 0.25     |
| 0.4023        | 8.0   | 24   | 0.7981          | 0.25     |
| 0.3556        | 9.0   | 27   | 0.8110          | 0.25     |
| 0.2714        | 10.0  | 30   | 0.8269          | 0.25     |
| 0.2295        | 11.0  | 33   | 0.8276          | 0.25     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base__sst2__all-train
  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. -->

# deberta-v3-base__sst2__all-train

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6964
- Accuracy: 0.49

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 7    | 0.6964          | 0.49     |
| No log        | 2.0   | 14   | 0.7010          | 0.49     |
| No log        | 3.0   | 21   | 0.7031          | 0.49     |
| No log        | 4.0   | 28   | 0.7054          | 0.49     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-5
  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. -->

# distilbert-base-uncased__sst2__train-32-5

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6248
- Accuracy: 0.6826

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7136        | 1.0   | 13   | 0.6850          | 0.5385   |
| 0.6496        | 2.0   | 26   | 0.6670          | 0.6154   |
| 0.5895        | 3.0   | 39   | 0.6464          | 0.7692   |
| 0.4271        | 4.0   | 52   | 0.6478          | 0.7692   |
| 0.2182        | 5.0   | 65   | 0.6809          | 0.6923   |
| 0.103         | 6.0   | 78   | 0.9119          | 0.6923   |
| 0.0326        | 7.0   | 91   | 1.0718          | 0.6923   |
| 0.0154        | 8.0   | 104  | 1.0721          | 0.7692   |
| 0.0087        | 9.0   | 117  | 1.1416          | 0.7692   |
| 0.0067        | 10.0  | 130  | 1.2088          | 0.7692   |
| 0.005         | 11.0  | 143  | 1.2656          | 0.7692   |
| 0.0037        | 12.0  | 156  | 1.3104          | 0.7692   |
| 0.0032        | 13.0  | 169  | 1.3428          | 0.6923   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-0
  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. -->

# distilbert-base-uncased__subj__train-8-0

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4440
- Accuracy: 0.789

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7163        | 1.0   | 3    | 0.6868          | 0.5      |
| 0.6683        | 2.0   | 6    | 0.6804          | 0.75     |
| 0.6375        | 3.0   | 9    | 0.6702          | 0.75     |
| 0.5997        | 4.0   | 12   | 0.6686          | 0.75     |
| 0.5345        | 5.0   | 15   | 0.6720          | 0.75     |
| 0.4673        | 6.0   | 18   | 0.6646          | 0.75     |
| 0.4214        | 7.0   | 21   | 0.6494          | 0.75     |
| 0.3439        | 8.0   | 24   | 0.6313          | 0.75     |
| 0.3157        | 9.0   | 27   | 0.6052          | 0.75     |
| 0.2329        | 10.0  | 30   | 0.5908          | 0.75     |
| 0.1989        | 11.0  | 33   | 0.5768          | 0.75     |
| 0.1581        | 12.0  | 36   | 0.5727          | 0.75     |
| 0.1257        | 13.0  | 39   | 0.5678          | 0.75     |
| 0.1005        | 14.0  | 42   | 0.5518          | 0.75     |
| 0.0836        | 15.0  | 45   | 0.5411          | 0.75     |
| 0.0611        | 16.0  | 48   | 0.5320          | 0.75     |
| 0.0503        | 17.0  | 51   | 0.5299          | 0.75     |
| 0.0407        | 18.0  | 54   | 0.5368          | 0.75     |
| 0.0332        | 19.0  | 57   | 0.5455          | 0.75     |
| 0.0293        | 20.0  | 60   | 0.5525          | 0.75     |
| 0.0254        | 21.0  | 63   | 0.5560          | 0.75     |
| 0.0231        | 22.0  | 66   | 0.5569          | 0.75     |
| 0.0201        | 23.0  | 69   | 0.5572          | 0.75     |
| 0.0179        | 24.0  | 72   | 0.5575          | 0.75     |
| 0.0184        | 25.0  | 75   | 0.5547          | 0.75     |
| 0.0148        | 26.0  | 78   | 0.5493          | 0.75     |
| 0.0149        | 27.0  | 81   | 0.5473          | 0.75     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-9
  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. -->

# distilbert-base-uncased__subj__train-8-9

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4865
- Accuracy: 0.778

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7024        | 1.0   | 3    | 0.6843          | 0.75     |
| 0.67          | 2.0   | 6    | 0.6807          | 0.5      |
| 0.6371        | 3.0   | 9    | 0.6677          | 0.5      |
| 0.585         | 4.0   | 12   | 0.6649          | 0.5      |
| 0.5122        | 5.0   | 15   | 0.6707          | 0.5      |
| 0.4379        | 6.0   | 18   | 0.6660          | 0.5      |
| 0.4035        | 7.0   | 21   | 0.6666          | 0.5      |
| 0.323         | 8.0   | 24   | 0.6672          | 0.5      |
| 0.2841        | 9.0   | 27   | 0.6534          | 0.5      |
| 0.21          | 10.0  | 30   | 0.6456          | 0.5      |
| 0.1735        | 11.0  | 33   | 0.6325          | 0.5      |
| 0.133         | 12.0  | 36   | 0.6214          | 0.5      |
| 0.0986        | 13.0  | 39   | 0.6351          | 0.5      |
| 0.081         | 14.0  | 42   | 0.6495          | 0.5      |
| 0.0638        | 15.0  | 45   | 0.6671          | 0.5      |
| 0.0449        | 16.0  | 48   | 0.7156          | 0.5      |
| 0.0399        | 17.0  | 51   | 0.7608          | 0.5      |
| 0.0314        | 18.0  | 54   | 0.7796          | 0.5      |
| 0.0243        | 19.0  | 57   | 0.7789          | 0.5      |
| 0.0227        | 20.0  | 60   | 0.7684          | 0.5      |
| 0.0221        | 21.0  | 63   | 0.7628          | 0.5      |
| 0.0192        | 22.0  | 66   | 0.7728          | 0.5      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-8
  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. -->

# distilbert-base-uncased__sst2__train-8-8

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6925
- Accuracy: 0.5200

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7061        | 1.0   | 3    | 0.6899          | 0.75     |
| 0.6627        | 2.0   | 6    | 0.7026          | 0.25     |
| 0.644         | 3.0   | 9    | 0.7158          | 0.25     |
| 0.6087        | 4.0   | 12   | 0.7325          | 0.25     |
| 0.5602        | 5.0   | 15   | 0.7555          | 0.25     |
| 0.5034        | 6.0   | 18   | 0.7725          | 0.25     |
| 0.4672        | 7.0   | 21   | 0.7983          | 0.25     |
| 0.403         | 8.0   | 24   | 0.8314          | 0.25     |
| 0.3571        | 9.0   | 27   | 0.8555          | 0.25     |
| 0.2792        | 10.0  | 30   | 0.9065          | 0.25     |
| 0.2373        | 11.0  | 33   | 0.9286          | 0.25     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-1
  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. -->

# distilbert-base-uncased__sst2__train-8-1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6930
- Accuracy: 0.5047

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7082        | 1.0   | 3    | 0.7048          | 0.25     |
| 0.6761        | 2.0   | 6    | 0.7249          | 0.25     |
| 0.6653        | 3.0   | 9    | 0.7423          | 0.25     |
| 0.6212        | 4.0   | 12   | 0.7727          | 0.25     |
| 0.5932        | 5.0   | 15   | 0.8098          | 0.25     |
| 0.5427        | 6.0   | 18   | 0.8496          | 0.25     |
| 0.5146        | 7.0   | 21   | 0.8992          | 0.25     |
| 0.4356        | 8.0   | 24   | 0.9494          | 0.25     |
| 0.4275        | 9.0   | 27   | 0.9694          | 0.25     |
| 0.3351        | 10.0  | 30   | 0.9968          | 0.25     |
| 0.2812        | 11.0  | 33   | 1.0056          | 0.5      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MiniLM-L12-H384-uncased__sst2__all-train
  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. -->

# MiniLM-L12-H384-uncased__sst2__all-train

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2632
- Accuracy: 0.9055

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4183        | 1.0   | 433  | 0.3456          | 0.8720   |
| 0.2714        | 2.0   | 866  | 0.2632          | 0.9055   |
| 0.2016        | 3.0   | 1299 | 0.3357          | 0.8990   |
| 0.1501        | 4.0   | 1732 | 0.4474          | 0.8863   |
| 0.1119        | 5.0   | 2165 | 0.3998          | 0.8979   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-7
  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. -->

# distilbert-base-uncased__subj__train-8-7

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2766
- Accuracy: 0.8845

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7044        | 1.0   | 3    | 0.6909          | 0.5      |
| 0.6678        | 2.0   | 6    | 0.6901          | 0.5      |
| 0.6336        | 3.0   | 9    | 0.6807          | 0.5      |
| 0.5926        | 4.0   | 12   | 0.6726          | 0.5      |
| 0.5221        | 5.0   | 15   | 0.6648          | 0.5      |
| 0.4573        | 6.0   | 18   | 0.6470          | 0.5      |
| 0.4177        | 7.0   | 21   | 0.6251          | 0.5      |
| 0.3252        | 8.0   | 24   | 0.5994          | 0.5      |
| 0.2831        | 9.0   | 27   | 0.5529          | 0.5      |
| 0.213         | 10.0  | 30   | 0.5078          | 0.75     |
| 0.1808        | 11.0  | 33   | 0.4521          | 1.0      |
| 0.1355        | 12.0  | 36   | 0.3996          | 1.0      |
| 0.1027        | 13.0  | 39   | 0.3557          | 1.0      |
| 0.0862        | 14.0  | 42   | 0.3121          | 1.0      |
| 0.0682        | 15.0  | 45   | 0.2828          | 1.0      |
| 0.0517        | 16.0  | 48   | 0.2603          | 1.0      |
| 0.0466        | 17.0  | 51   | 0.2412          | 1.0      |
| 0.038         | 18.0  | 54   | 0.2241          | 1.0      |
| 0.0276        | 19.0  | 57   | 0.2096          | 1.0      |
| 0.0246        | 20.0  | 60   | 0.1969          | 1.0      |
| 0.0249        | 21.0  | 63   | 0.1859          | 1.0      |
| 0.0201        | 22.0  | 66   | 0.1770          | 1.0      |
| 0.018         | 23.0  | 69   | 0.1703          | 1.0      |
| 0.0164        | 24.0  | 72   | 0.1670          | 1.0      |
| 0.0172        | 25.0  | 75   | 0.1639          | 1.0      |
| 0.0135        | 26.0  | 78   | 0.1604          | 1.0      |
| 0.014         | 27.0  | 81   | 0.1585          | 1.0      |
| 0.0108        | 28.0  | 84   | 0.1569          | 1.0      |
| 0.0116        | 29.0  | 87   | 0.1549          | 1.0      |
| 0.0111        | 30.0  | 90   | 0.1532          | 1.0      |
| 0.0113        | 31.0  | 93   | 0.1513          | 1.0      |
| 0.0104        | 32.0  | 96   | 0.1503          | 1.0      |
| 0.01          | 33.0  | 99   | 0.1490          | 1.0      |
| 0.0079        | 34.0  | 102  | 0.1479          | 1.0      |
| 0.0097        | 35.0  | 105  | 0.1466          | 1.0      |
| 0.0112        | 36.0  | 108  | 0.1458          | 1.0      |
| 0.0091        | 37.0  | 111  | 0.1457          | 1.0      |
| 0.0098        | 38.0  | 114  | 0.1454          | 1.0      |
| 0.0076        | 39.0  | 117  | 0.1451          | 1.0      |
| 0.0085        | 40.0  | 120  | 0.1448          | 1.0      |
| 0.0079        | 41.0  | 123  | 0.1445          | 1.0      |
| 0.0096        | 42.0  | 126  | 0.1440          | 1.0      |
| 0.0081        | 43.0  | 129  | 0.1430          | 1.0      |
| 0.0083        | 44.0  | 132  | 0.1424          | 1.0      |
| 0.0088        | 45.0  | 135  | 0.1418          | 1.0      |
| 0.0077        | 46.0  | 138  | 0.1414          | 1.0      |
| 0.0073        | 47.0  | 141  | 0.1413          | 1.0      |
| 0.0084        | 48.0  | 144  | 0.1412          | 1.0      |
| 0.0072        | 49.0  | 147  | 0.1411          | 1.0      |
| 0.0077        | 50.0  | 150  | 0.1411          | 1.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-16-5
  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. -->

# distilbert-base-uncased__sst2__train-16-5

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6537
- Accuracy: 0.6332

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6925        | 1.0   | 7    | 0.6966          | 0.2857   |
| 0.6703        | 2.0   | 14   | 0.7045          | 0.2857   |
| 0.6404        | 3.0   | 21   | 0.7205          | 0.2857   |
| 0.555         | 4.0   | 28   | 0.7548          | 0.2857   |
| 0.5179        | 5.0   | 35   | 0.6745          | 0.5714   |
| 0.3038        | 6.0   | 42   | 0.7260          | 0.5714   |
| 0.2089        | 7.0   | 49   | 0.8016          | 0.5714   |
| 0.1303        | 8.0   | 56   | 0.8202          | 0.5714   |
| 0.0899        | 9.0   | 63   | 0.9966          | 0.5714   |
| 0.0552        | 10.0  | 70   | 1.1887          | 0.5714   |
| 0.0333        | 11.0  | 77   | 1.2163          | 0.5714   |
| 0.0169        | 12.0  | 84   | 1.2874          | 0.5714   |
| 0.0136        | 13.0  | 91   | 1.3598          | 0.5714   |
| 0.0103        | 14.0  | 98   | 1.4237          | 0.5714   |
| 0.0089        | 15.0  | 105  | 1.4758          | 0.5714   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-3
  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. -->

# distilbert-base-uncased__sst2__train-32-3

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5694
- Accuracy: 0.7073

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7118        | 1.0   | 13   | 0.6844          | 0.5385   |
| 0.6587        | 2.0   | 26   | 0.6707          | 0.6154   |
| 0.6067        | 3.0   | 39   | 0.6295          | 0.5385   |
| 0.4714        | 4.0   | 52   | 0.5811          | 0.6923   |
| 0.2444        | 5.0   | 65   | 0.5932          | 0.7692   |
| 0.1007        | 6.0   | 78   | 0.7386          | 0.6923   |
| 0.0332        | 7.0   | 91   | 0.6962          | 0.6154   |
| 0.0147        | 8.0   | 104  | 0.8200          | 0.7692   |
| 0.0083        | 9.0   | 117  | 0.9250          | 0.7692   |
| 0.0066        | 10.0  | 130  | 0.9345          | 0.7692   |
| 0.005         | 11.0  | 143  | 0.9313          | 0.7692   |
| 0.0036        | 12.0  | 156  | 0.9356          | 0.7692   |
| 0.0031        | 13.0  | 169  | 0.9395          | 0.7692   |
| 0.0029        | 14.0  | 182  | 0.9504          | 0.7692   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-9
  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. -->

# distilbert-base-uncased__sst2__train-32-9

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5625
- Accuracy: 0.7353

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7057        | 1.0   | 13   | 0.6805          | 0.5385   |
| 0.6642        | 2.0   | 26   | 0.6526          | 0.7692   |
| 0.5869        | 3.0   | 39   | 0.5773          | 0.8462   |
| 0.4085        | 4.0   | 52   | 0.4959          | 0.8462   |
| 0.2181        | 5.0   | 65   | 0.4902          | 0.6923   |
| 0.069         | 6.0   | 78   | 0.5065          | 0.8462   |
| 0.0522        | 7.0   | 91   | 0.6082          | 0.7692   |
| 0.0135        | 8.0   | 104  | 0.6924          | 0.7692   |
| 0.0084        | 9.0   | 117  | 0.5921          | 0.7692   |
| 0.0061        | 10.0  | 130  | 0.6477          | 0.7692   |
| 0.0047        | 11.0  | 143  | 0.6648          | 0.7692   |
| 0.0035        | 12.0  | 156  | 0.6640          | 0.7692   |
| 0.0031        | 13.0  | 169  | 0.6615          | 0.7692   |
| 0.0029        | 14.0  | 182  | 0.6605          | 0.7692   |
| 0.0026        | 15.0  | 195  | 0.6538          | 0.8462   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-0
  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. -->

# distilbert-base-uncased__hate_speech_offensive__train-8-0

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1097
- Accuracy: 0.132

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1065        | 1.0   | 5    | 1.1287          | 0.0      |
| 1.0592        | 2.0   | 10   | 1.1729          | 0.0      |
| 1.0059        | 3.0   | 15   | 1.1959          | 0.0      |
| 0.9129        | 4.0   | 20   | 1.2410          | 0.0      |
| 0.8231        | 5.0   | 25   | 1.2820          | 0.0      |
| 0.7192        | 6.0   | 30   | 1.3361          | 0.0      |
| 0.6121        | 7.0   | 35   | 1.4176          | 0.0      |
| 0.5055        | 8.0   | 40   | 1.5111          | 0.0      |
| 0.4002        | 9.0   | 45   | 1.5572          | 0.0      |
| 0.3788        | 10.0  | 50   | 1.6733          | 0.0      |
| 0.2755        | 11.0  | 55   | 1.7381          | 0.2      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-7
  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. -->

# distilbert-base-uncased__sst2__train-8-7

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6950
- Accuracy: 0.4618

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7156        | 1.0   | 3    | 0.6965          | 0.25     |
| 0.6645        | 2.0   | 6    | 0.7059          | 0.25     |
| 0.6368        | 3.0   | 9    | 0.7179          | 0.25     |
| 0.5944        | 4.0   | 12   | 0.7408          | 0.25     |
| 0.5369        | 5.0   | 15   | 0.7758          | 0.25     |
| 0.449         | 6.0   | 18   | 0.8009          | 0.25     |
| 0.4352        | 7.0   | 21   | 0.8209          | 0.5      |
| 0.3462        | 8.0   | 24   | 0.8470          | 0.5      |
| 0.3028        | 9.0   | 27   | 0.8579          | 0.5      |
| 0.2365        | 10.0  | 30   | 0.8704          | 0.5      |
| 0.2023        | 11.0  | 33   | 0.8770          | 0.5      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-4
  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. -->

# distilbert-base-uncased__subj__train-8-4

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3305
- Accuracy: 0.8565

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6991        | 1.0   | 3    | 0.6772          | 0.75     |
| 0.6707        | 2.0   | 6    | 0.6704          | 0.75     |
| 0.6402        | 3.0   | 9    | 0.6608          | 1.0      |
| 0.5789        | 4.0   | 12   | 0.6547          | 0.75     |
| 0.5211        | 5.0   | 15   | 0.6434          | 0.75     |
| 0.454         | 6.0   | 18   | 0.6102          | 1.0      |
| 0.4187        | 7.0   | 21   | 0.5701          | 1.0      |
| 0.3401        | 8.0   | 24   | 0.5289          | 1.0      |
| 0.3107        | 9.0   | 27   | 0.4737          | 1.0      |
| 0.2381        | 10.0  | 30   | 0.4255          | 1.0      |
| 0.1982        | 11.0  | 33   | 0.3685          | 1.0      |
| 0.1631        | 12.0  | 36   | 0.3200          | 1.0      |
| 0.1234        | 13.0  | 39   | 0.2798          | 1.0      |
| 0.0993        | 14.0  | 42   | 0.2455          | 1.0      |
| 0.0781        | 15.0  | 45   | 0.2135          | 1.0      |
| 0.0586        | 16.0  | 48   | 0.1891          | 1.0      |
| 0.0513        | 17.0  | 51   | 0.1671          | 1.0      |
| 0.043         | 18.0  | 54   | 0.1427          | 1.0      |
| 0.0307        | 19.0  | 57   | 0.1225          | 1.0      |
| 0.0273        | 20.0  | 60   | 0.1060          | 1.0      |
| 0.0266        | 21.0  | 63   | 0.0920          | 1.0      |
| 0.0233        | 22.0  | 66   | 0.0823          | 1.0      |
| 0.0185        | 23.0  | 69   | 0.0751          | 1.0      |
| 0.0173        | 24.0  | 72   | 0.0698          | 1.0      |
| 0.0172        | 25.0  | 75   | 0.0651          | 1.0      |
| 0.0142        | 26.0  | 78   | 0.0613          | 1.0      |
| 0.0151        | 27.0  | 81   | 0.0583          | 1.0      |
| 0.0117        | 28.0  | 84   | 0.0563          | 1.0      |
| 0.0123        | 29.0  | 87   | 0.0546          | 1.0      |
| 0.0121        | 30.0  | 90   | 0.0531          | 1.0      |
| 0.0123        | 31.0  | 93   | 0.0511          | 1.0      |
| 0.0112        | 32.0  | 96   | 0.0496          | 1.0      |
| 0.0103        | 33.0  | 99   | 0.0481          | 1.0      |
| 0.0086        | 34.0  | 102  | 0.0468          | 1.0      |
| 0.0096        | 35.0  | 105  | 0.0457          | 1.0      |
| 0.0107        | 36.0  | 108  | 0.0447          | 1.0      |
| 0.0095        | 37.0  | 111  | 0.0439          | 1.0      |
| 0.0102        | 38.0  | 114  | 0.0429          | 1.0      |
| 0.0077        | 39.0  | 117  | 0.0422          | 1.0      |
| 0.0092        | 40.0  | 120  | 0.0415          | 1.0      |
| 0.0083        | 41.0  | 123  | 0.0409          | 1.0      |
| 0.0094        | 42.0  | 126  | 0.0404          | 1.0      |
| 0.0084        | 43.0  | 129  | 0.0400          | 1.0      |
| 0.0085        | 44.0  | 132  | 0.0396          | 1.0      |
| 0.0092        | 45.0  | 135  | 0.0392          | 1.0      |
| 0.0076        | 46.0  | 138  | 0.0389          | 1.0      |
| 0.0073        | 47.0  | 141  | 0.0388          | 1.0      |
| 0.0085        | 48.0  | 144  | 0.0387          | 1.0      |
| 0.0071        | 49.0  | 147  | 0.0386          | 1.0      |
| 0.0079        | 50.0  | 150  | 0.0386          | 1.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-8
  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. -->

# distilbert-base-uncased__sst2__train-32-8

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6880
- Accuracy: 0.5014

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.712         | 1.0   | 13   | 0.6936          | 0.5385   |
| 0.665         | 2.0   | 26   | 0.6960          | 0.3846   |
| 0.6112        | 3.0   | 39   | 0.7138          | 0.3846   |
| 0.4521        | 4.0   | 52   | 0.8243          | 0.4615   |
| 0.2627        | 5.0   | 65   | 0.7723          | 0.6154   |
| 0.0928        | 6.0   | 78   | 1.2666          | 0.5385   |
| 0.0312        | 7.0   | 91   | 1.2306          | 0.6154   |
| 0.0132        | 8.0   | 104  | 1.3385          | 0.6154   |
| 0.0082        | 9.0   | 117  | 1.4584          | 0.6154   |
| 0.0063        | 10.0  | 130  | 1.5429          | 0.6154   |
| 0.0049        | 11.0  | 143  | 1.5913          | 0.6154   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-32-6
  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. -->

# distilbert-base-uncased__sst2__train-32-6

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5072
- Accuracy: 0.7650

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7057        | 1.0   | 13   | 0.6704          | 0.6923   |
| 0.6489        | 2.0   | 26   | 0.6228          | 0.8462   |
| 0.5475        | 3.0   | 39   | 0.5079          | 0.8462   |
| 0.4014        | 4.0   | 52   | 0.4203          | 0.8462   |
| 0.1923        | 5.0   | 65   | 0.3872          | 0.8462   |
| 0.1014        | 6.0   | 78   | 0.4909          | 0.8462   |
| 0.0349        | 7.0   | 91   | 0.5460          | 0.8462   |
| 0.0173        | 8.0   | 104  | 0.4867          | 0.8462   |
| 0.0098        | 9.0   | 117  | 0.5274          | 0.8462   |
| 0.0075        | 10.0  | 130  | 0.6086          | 0.8462   |
| 0.0057        | 11.0  | 143  | 0.6604          | 0.8462   |
| 0.0041        | 12.0  | 156  | 0.6904          | 0.8462   |
| 0.0037        | 13.0  | 169  | 0.7164          | 0.8462   |
| 0.0034        | 14.0  | 182  | 0.7368          | 0.8462   |
| 0.0031        | 15.0  | 195  | 0.7565          | 0.8462   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-0
  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. -->

# deberta-v3-large__sst2__train-8-0

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7088
- Accuracy: 0.5008

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6705        | 1.0   | 3    | 0.7961          | 0.25     |
| 0.6571        | 2.0   | 6    | 0.8092          | 0.25     |
| 0.7043        | 3.0   | 9    | 0.7977          | 0.25     |
| 0.6207        | 4.0   | 12   | 0.8478          | 0.25     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__all-train
  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. -->

# distilbert-base-uncased__subj__all-train

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3193
- Accuracy: 0.9485

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1992        | 1.0   | 500  | 0.1236          | 0.963    |
| 0.084         | 2.0   | 1000 | 0.1428          | 0.963    |
| 0.0333        | 3.0   | 1500 | 0.1906          | 0.965    |
| 0.0159        | 4.0   | 2000 | 0.3193          | 0.9485   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__all-train
  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. -->

# distilbert-base-uncased__sst2__all-train

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2496
- Accuracy: 0.8962

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3643        | 1.0   | 433  | 0.2496          | 0.8962   |
| 0.196         | 2.0   | 866  | 0.2548          | 0.9110   |
| 0.0915        | 3.0   | 1299 | 0.4483          | 0.8957   |
| 0.0505        | 4.0   | 1732 | 0.4968          | 0.9044   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-7
  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. -->

# distilbert-base-uncased__hate_speech_offensive__train-8-7

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1206
- Accuracy: 0.0555

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1186        | 1.0   | 5    | 1.1631          | 0.0      |
| 1.058         | 2.0   | 10   | 1.1986          | 0.0      |
| 1.081         | 3.0   | 15   | 1.2111          | 0.0      |
| 1.0118        | 4.0   | 20   | 1.2373          | 0.0      |
| 0.9404        | 5.0   | 25   | 1.2645          | 0.0      |
| 0.9146        | 6.0   | 30   | 1.3258          | 0.0      |
| 0.8285        | 7.0   | 35   | 1.3789          | 0.0      |
| 0.6422        | 8.0   | 40   | 1.3783          | 0.0      |
| 0.6156        | 9.0   | 45   | 1.3691          | 0.0      |
| 0.5321        | 10.0  | 50   | 1.3693          | 0.0      |
| 0.4504        | 11.0  | 55   | 1.4000          | 0.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-16-9
  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. -->

# distilbert-base-uncased__sst2__train-16-9

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6915
- Accuracy: 0.5157

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6868        | 1.0   | 7    | 0.7121          | 0.1429   |
| 0.6755        | 2.0   | 14   | 0.7234          | 0.1429   |
| 0.6389        | 3.0   | 21   | 0.7384          | 0.2857   |
| 0.5575        | 4.0   | 28   | 0.7884          | 0.2857   |
| 0.4972        | 5.0   | 35   | 0.7767          | 0.4286   |
| 0.2821        | 6.0   | 42   | 0.8275          | 0.4286   |
| 0.1859        | 7.0   | 49   | 0.9283          | 0.2857   |
| 0.1388        | 8.0   | 56   | 0.9384          | 0.4286   |
| 0.078         | 9.0   | 63   | 1.1973          | 0.4286   |
| 0.0462        | 10.0  | 70   | 1.4016          | 0.4286   |
| 0.0319        | 11.0  | 77   | 1.4087          | 0.4286   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-6
  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. -->

# distilbert-base-uncased__sst2__train-8-6

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5336
- Accuracy: 0.7523

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7161        | 1.0   | 3    | 0.6941          | 0.5      |
| 0.6786        | 2.0   | 6    | 0.7039          | 0.25     |
| 0.6586        | 3.0   | 9    | 0.7090          | 0.25     |
| 0.6121        | 4.0   | 12   | 0.7183          | 0.25     |
| 0.5696        | 5.0   | 15   | 0.7266          | 0.25     |
| 0.522         | 6.0   | 18   | 0.7305          | 0.25     |
| 0.4899        | 7.0   | 21   | 0.7339          | 0.25     |
| 0.3985        | 8.0   | 24   | 0.7429          | 0.25     |
| 0.3758        | 9.0   | 27   | 0.7224          | 0.25     |
| 0.2876        | 10.0  | 30   | 0.7068          | 0.5      |
| 0.2498        | 11.0  | 33   | 0.6751          | 0.75     |
| 0.1921        | 12.0  | 36   | 0.6487          | 0.75     |
| 0.1491        | 13.0  | 39   | 0.6261          | 0.75     |
| 0.1276        | 14.0  | 42   | 0.6102          | 0.75     |
| 0.0996        | 15.0  | 45   | 0.5964          | 0.75     |
| 0.073         | 16.0  | 48   | 0.6019          | 0.75     |
| 0.0627        | 17.0  | 51   | 0.5933          | 0.75     |
| 0.053         | 18.0  | 54   | 0.5768          | 0.75     |
| 0.0403        | 19.0  | 57   | 0.5698          | 0.75     |
| 0.0328        | 20.0  | 60   | 0.5656          | 0.75     |
| 0.03          | 21.0  | 63   | 0.5634          | 0.75     |
| 0.025         | 22.0  | 66   | 0.5620          | 0.75     |
| 0.0209        | 23.0  | 69   | 0.5623          | 0.75     |
| 0.0214        | 24.0  | 72   | 0.5606          | 0.75     |
| 0.0191        | 25.0  | 75   | 0.5565          | 0.75     |
| 0.0173        | 26.0  | 78   | 0.5485          | 0.75     |
| 0.0175        | 27.0  | 81   | 0.5397          | 0.75     |
| 0.0132        | 28.0  | 84   | 0.5322          | 0.75     |
| 0.0138        | 29.0  | 87   | 0.5241          | 0.75     |
| 0.0128        | 30.0  | 90   | 0.5235          | 0.75     |
| 0.0126        | 31.0  | 93   | 0.5253          | 0.75     |
| 0.012         | 32.0  | 96   | 0.5317          | 0.75     |
| 0.0118        | 33.0  | 99   | 0.5342          | 0.75     |
| 0.0092        | 34.0  | 102  | 0.5388          | 0.75     |
| 0.0117        | 35.0  | 105  | 0.5414          | 0.75     |
| 0.0124        | 36.0  | 108  | 0.5453          | 0.75     |
| 0.0109        | 37.0  | 111  | 0.5506          | 0.75     |
| 0.0112        | 38.0  | 114  | 0.5555          | 0.75     |
| 0.0087        | 39.0  | 117  | 0.5597          | 0.75     |
| 0.01          | 40.0  | 120  | 0.5640          | 0.75     |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__subj__train-8-6
  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. -->

# distilbert-base-uncased__subj__train-8-6

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6075
- Accuracy: 0.7485

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7163        | 1.0   | 3    | 0.6923          | 0.5      |
| 0.6648        | 2.0   | 6    | 0.6838          | 0.5      |
| 0.6329        | 3.0   | 9    | 0.6747          | 0.75     |
| 0.5836        | 4.0   | 12   | 0.6693          | 0.5      |
| 0.5287        | 5.0   | 15   | 0.6670          | 0.25     |
| 0.4585        | 6.0   | 18   | 0.6517          | 0.5      |
| 0.415         | 7.0   | 21   | 0.6290          | 0.5      |
| 0.3353        | 8.0   | 24   | 0.6019          | 0.5      |
| 0.2841        | 9.0   | 27   | 0.5613          | 0.75     |
| 0.2203        | 10.0  | 30   | 0.5222          | 1.0      |
| 0.1743        | 11.0  | 33   | 0.4769          | 1.0      |
| 0.1444        | 12.0  | 36   | 0.4597          | 1.0      |
| 0.1079        | 13.0  | 39   | 0.4462          | 1.0      |
| 0.0891        | 14.0  | 42   | 0.4216          | 1.0      |
| 0.0704        | 15.0  | 45   | 0.3880          | 1.0      |
| 0.0505        | 16.0  | 48   | 0.3663          | 1.0      |
| 0.0428        | 17.0  | 51   | 0.3536          | 1.0      |
| 0.0356        | 18.0  | 54   | 0.3490          | 1.0      |
| 0.0283        | 19.0  | 57   | 0.3531          | 1.0      |
| 0.025         | 20.0  | 60   | 0.3595          | 1.0      |
| 0.0239        | 21.0  | 63   | 0.3594          | 1.0      |
| 0.0202        | 22.0  | 66   | 0.3521          | 1.0      |
| 0.0168        | 23.0  | 69   | 0.3475          | 1.0      |
| 0.0159        | 24.0  | 72   | 0.3458          | 1.0      |
| 0.0164        | 25.0  | 75   | 0.3409          | 1.0      |
| 0.0132        | 26.0  | 78   | 0.3360          | 1.0      |
| 0.0137        | 27.0  | 81   | 0.3302          | 1.0      |
| 0.0112        | 28.0  | 84   | 0.3235          | 1.0      |
| 0.0113        | 29.0  | 87   | 0.3178          | 1.0      |
| 0.0111        | 30.0  | 90   | 0.3159          | 1.0      |
| 0.0113        | 31.0  | 93   | 0.3108          | 1.0      |
| 0.0107        | 32.0  | 96   | 0.3101          | 1.0      |
| 0.0101        | 33.0  | 99   | 0.3100          | 1.0      |
| 0.0083        | 34.0  | 102  | 0.3110          | 1.0      |
| 0.0092        | 35.0  | 105  | 0.3117          | 1.0      |
| 0.0102        | 36.0  | 108  | 0.3104          | 1.0      |
| 0.0086        | 37.0  | 111  | 0.3086          | 1.0      |
| 0.0092        | 38.0  | 114  | 0.3047          | 1.0      |
| 0.0072        | 39.0  | 117  | 0.3024          | 1.0      |
| 0.0079        | 40.0  | 120  | 0.3014          | 1.0      |
| 0.0079        | 41.0  | 123  | 0.2983          | 1.0      |
| 0.0091        | 42.0  | 126  | 0.2948          | 1.0      |
| 0.0077        | 43.0  | 129  | 0.2915          | 1.0      |
| 0.0085        | 44.0  | 132  | 0.2890          | 1.0      |
| 0.009         | 45.0  | 135  | 0.2870          | 1.0      |
| 0.0073        | 46.0  | 138  | 0.2856          | 1.0      |
| 0.0073        | 47.0  | 141  | 0.2844          | 1.0      |
| 0.0076        | 48.0  | 144  | 0.2841          | 1.0      |
| 0.0065        | 49.0  | 147  | 0.2836          | 1.0      |
| 0.0081        | 50.0  | 150  | 0.2835          | 1.0      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__hate_speech_offensive__train-8-8
  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. -->

# distilbert-base-uncased__hate_speech_offensive__train-8-8

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0005
- Accuracy: 0.518

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1029        | 1.0   | 5    | 1.1295          | 0.0      |
| 1.0472        | 2.0   | 10   | 1.1531          | 0.0      |
| 1.054         | 3.0   | 15   | 1.1475          | 0.0      |
| 0.9366        | 4.0   | 20   | 1.1515          | 0.0      |
| 0.8698        | 5.0   | 25   | 1.1236          | 0.4      |
| 0.8148        | 6.0   | 30   | 1.0716          | 0.6      |
| 0.6884        | 7.0   | 35   | 1.0662          | 0.6      |
| 0.5641        | 8.0   | 40   | 1.0671          | 0.6      |
| 0.5           | 9.0   | 45   | 1.0282          | 0.6      |
| 0.3882        | 10.0  | 50   | 1.0500          | 0.6      |
| 0.3522        | 11.0  | 55   | 1.1381          | 0.6      |
| 0.2492        | 12.0  | 60   | 1.1278          | 0.6      |
| 0.2063        | 13.0  | 65   | 1.0731          | 0.6      |
| 0.1608        | 14.0  | 70   | 1.1339          | 0.6      |
| 0.1448        | 15.0  | 75   | 1.1892          | 0.6      |
| 0.0925        | 16.0  | 80   | 1.1840          | 0.6      |
| 0.0768        | 17.0  | 85   | 1.0608          | 0.6      |
| 0.0585        | 18.0  | 90   | 1.1073          | 0.6      |
| 0.0592        | 19.0  | 95   | 1.3134          | 0.6      |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3


---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-16-1
  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. -->

# distilbert-base-uncased__sst2__train-16-1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6012
- Accuracy: 0.6766

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6983        | 1.0   | 7    | 0.7036          | 0.2857   |
| 0.6836        | 2.0   | 14   | 0.7181          | 0.2857   |
| 0.645         | 3.0   | 21   | 0.7381          | 0.2857   |
| 0.5902        | 4.0   | 28   | 0.7746          | 0.2857   |
| 0.5799        | 5.0   | 35   | 0.7242          | 0.5714   |
| 0.3584        | 6.0   | 42   | 0.6935          | 0.5714   |
| 0.2596        | 7.0   | 49   | 0.7041          | 0.5714   |
| 0.1815        | 8.0   | 56   | 0.5930          | 0.7143   |
| 0.0827        | 9.0   | 63   | 0.6976          | 0.7143   |
| 0.0613        | 10.0  | 70   | 0.7346          | 0.7143   |
| 0.0356        | 11.0  | 77   | 0.6992          | 0.5714   |
| 0.0158        | 12.0  | 84   | 0.7328          | 0.5714   |
| 0.013         | 13.0  | 91   | 0.7819          | 0.5714   |
| 0.0103        | 14.0  | 98   | 0.8589          | 0.5714   |
| 0.0087        | 15.0  | 105  | 0.9177          | 0.5714   |
| 0.0076        | 16.0  | 112  | 0.9519          | 0.5714   |
| 0.0078        | 17.0  | 119  | 0.9556          | 0.5714   |
| 0.006         | 18.0  | 126  | 0.9542          | 0.5714   |

### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3