
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# camembert_ccnet_classification_tools_NEFTune_fr

This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co/camembert/camembert-base-ccnet) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2866
- Accuracy: 0.95
- Learning Rate: 0.0

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.038         | 1.0   | 7    | 1.7370          | 0.65     | 0.0001 |
| 1.6169        | 2.0   | 14   | 1.2630          | 0.825    | 0.0001 |
| 1.1861        | 3.0   | 21   | 0.8659          | 0.95     | 0.0001 |
| 0.8284        | 4.0   | 28   | 0.6075          | 0.95     | 0.0001 |
| 0.6032        | 5.0   | 35   | 0.4207          | 0.975    | 0.0001 |
| 0.3928        | 6.0   | 42   | 0.3817          | 0.95     | 9e-05  |
| 0.2458        | 7.0   | 49   | 0.3378          | 0.95     | 0.0001 |
| 0.1683        | 8.0   | 56   | 0.4320          | 0.9      | 0.0001 |
| 0.127         | 9.0   | 63   | 0.3592          | 0.95     | 0.0001 |
| 0.0909        | 10.0  | 70   | 0.3695          | 0.925    | 0.0001 |
| 0.0719        | 11.0  | 77   | 0.3377          | 0.925    | 0.0001 |
| 0.0679        | 12.0  | 84   | 0.2450          | 0.95     | 8e-05  |
| 0.0865        | 13.0  | 91   | 0.2783          | 0.9      | 0.0001 |
| 0.0519        | 14.0  | 98   | 0.2265          | 0.975    | 0.0001 |
| 0.0497        | 15.0  | 105  | 0.2801          | 0.95     | 0.0001 |
| 0.0993        | 16.0  | 112  | 0.3733          | 0.925    | 0.0001 |
| 0.0358        | 17.0  | 119  | 0.4012          | 0.9      | 0.0001 |
| 0.0356        | 18.0  | 126  | 0.2591          | 0.95     | 7e-05  |
| 0.0279        | 19.0  | 133  | 0.2687          | 0.95     | 0.0001 |
| 0.0303        | 20.0  | 140  | 0.2650          | 0.95     | 0.0001 |
| 0.0246        | 21.0  | 147  | 0.2337          | 0.95     | 0.0001 |
| 0.0257        | 22.0  | 154  | 0.2274          | 0.95     | 0.0001 |
| 0.0448        | 23.0  | 161  | 0.2223          | 0.975    | 0.0001 |
| 0.0567        | 24.0  | 168  | 0.2157          | 0.975    | 6e-05  |
| 0.0182        | 25.0  | 175  | 0.2096          | 0.975    | 0.0001 |
| 0.0282        | 26.0  | 182  | 0.2118          | 0.975    | 0.0001 |
| 0.0232        | 27.0  | 189  | 0.2146          | 0.975    | 0.0001 |
| 0.0212        | 28.0  | 196  | 0.2162          | 0.975    | 0.0001 |
| 0.0197        | 29.0  | 203  | 0.2185          | 0.975    | 0.0001 |
| 0.0203        | 30.0  | 210  | 0.2215          | 0.975    | 5e-05  |
| 0.0172        | 31.0  | 217  | 0.2263          | 0.975    | 0.0000 |
| 0.0174        | 32.0  | 224  | 0.2347          | 0.975    | 0.0000 |
| 0.0152        | 33.0  | 231  | 0.2426          | 0.95     | 0.0000 |
| 0.0164        | 34.0  | 238  | 0.2443          | 0.95     | 0.0000 |
| 0.018         | 35.0  | 245  | 0.2557          | 0.95     | 0.0000 |
| 0.0328        | 36.0  | 252  | 0.2624          | 0.95     | 4e-05  |
| 0.0152        | 37.0  | 259  | 0.2602          | 0.95     | 0.0000 |
| 0.0147        | 38.0  | 266  | 0.2615          | 0.95     | 0.0000 |
| 0.0152        | 39.0  | 273  | 0.2634          | 0.95     | 0.0000 |
| 0.015         | 40.0  | 280  | 0.2699          | 0.95     | 0.0000 |
| 0.0147        | 41.0  | 287  | 0.2726          | 0.95     | 0.0000 |
| 0.0148        | 42.0  | 294  | 0.2783          | 0.95     | 3e-05  |
| 0.033         | 43.0  | 301  | 0.2793          | 0.95     | 0.0000 |
| 0.0143        | 44.0  | 308  | 0.2742          | 0.95     | 0.0000 |
| 0.0143        | 45.0  | 315  | 0.2681          | 0.95     | 0.0000 |
| 0.0139        | 46.0  | 322  | 0.2683          | 0.95     | 0.0000 |
| 0.0141        | 47.0  | 329  | 0.2706          | 0.95     | 0.0000 |
| 0.0132        | 48.0  | 336  | 0.2715          | 0.95     | 2e-05  |
| 0.0157        | 49.0  | 343  | 0.2785          | 0.95     | 0.0000 |
| 0.0142        | 50.0  | 350  | 0.2809          | 0.95     | 0.0000 |
| 0.0138        | 51.0  | 357  | 0.2818          | 0.95     | 0.0000 |
| 0.0141        | 52.0  | 364  | 0.2852          | 0.95     | 0.0000 |
| 0.015         | 53.0  | 371  | 0.2868          | 0.95     | 0.0000 |
| 0.0145        | 54.0  | 378  | 0.2876          | 0.95     | 1e-05  |
| 0.0135        | 55.0  | 385  | 0.2854          | 0.95     | 0.0000 |
| 0.0146        | 56.0  | 392  | 0.2862          | 0.95     | 0.0000 |
| 0.0136        | 57.0  | 399  | 0.2857          | 0.95     | 5e-06  |
| 0.014         | 58.0  | 406  | 0.2853          | 0.95     | 0.0000 |
| 0.0133        | 59.0  | 413  | 0.2862          | 0.95     | 0.0000 |
| 0.0125        | 60.0  | 420  | 0.2866          | 0.95     | 0.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "camembert/camembert-base-ccnet", "model-index": [{"name": "camembert_ccnet_classification_tools_NEFTune_fr", "results": []}]}
transformers pytorch camembert text-classification generated_from_trainer base_model:camembert/camembert-base-ccnet autotrain_compatible endpoints_compatible region:us