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# camembert_ccnet_classification_tools_classifier-only_fr_V2

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: 0.8155
- Accuracy: 0.7396
- Learning Rate: 0.0000

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.0589        | 1.0   | 15   | 2.0475          | 0.25     | 0.0001 |
| 2.0002        | 2.0   | 30   | 1.9708          | 0.3958   | 0.0001 |
| 1.9338        | 3.0   | 45   | 1.9353          | 0.3646   | 0.0001 |
| 1.8829        | 4.0   | 60   | 1.8915          | 0.3958   | 0.0001 |
| 1.8255        | 5.0   | 75   | 1.8285          | 0.4688   | 0.0001 |
| 1.79          | 6.0   | 90   | 1.7780          | 0.5833   | 9e-05  |
| 1.7391        | 7.0   | 105  | 1.7396          | 0.4688   | 0.0001 |
| 1.6838        | 8.0   | 120  | 1.6781          | 0.5417   | 0.0001 |
| 1.6385        | 9.0   | 135  | 1.6208          | 0.6042   | 0.0001 |
| 1.6083        | 10.0  | 150  | 1.5847          | 0.5729   | 0.0001 |
| 1.5543        | 11.0  | 165  | 1.5476          | 0.625    | 0.0001 |
| 1.5171        | 12.0  | 180  | 1.5068          | 0.6042   | 8e-05  |
| 1.4848        | 13.0  | 195  | 1.4651          | 0.6354   | 0.0001 |
| 1.4068        | 14.0  | 210  | 1.4436          | 0.6354   | 0.0001 |
| 1.4141        | 15.0  | 225  | 1.3965          | 0.6042   | 0.0001 |
| 1.3678        | 16.0  | 240  | 1.3565          | 0.6562   | 0.0001 |
| 1.309         | 17.0  | 255  | 1.3221          | 0.6875   | 0.0001 |
| 1.2867        | 18.0  | 270  | 1.2940          | 0.6667   | 7e-05  |
| 1.2667        | 19.0  | 285  | 1.2548          | 0.6667   | 0.0001 |
| 1.2271        | 20.0  | 300  | 1.2286          | 0.6875   | 0.0001 |
| 1.1865        | 21.0  | 315  | 1.1943          | 0.6875   | 0.0001 |
| 1.1691        | 22.0  | 330  | 1.1705          | 0.6979   | 0.0001 |
| 1.1502        | 23.0  | 345  | 1.1483          | 0.6875   | 0.0001 |
| 1.1195        | 24.0  | 360  | 1.1250          | 0.6875   | 6e-05  |
| 1.1148        | 25.0  | 375  | 1.1058          | 0.6979   | 0.0001 |
| 1.0893        | 26.0  | 390  | 1.0787          | 0.7083   | 0.0001 |
| 1.0736        | 27.0  | 405  | 1.0668          | 0.6979   | 0.0001 |
| 1.0303        | 28.0  | 420  | 1.0466          | 0.6979   | 0.0001 |
| 1.0475        | 29.0  | 435  | 1.0211          | 0.6979   | 0.0001 |
| 1.0122        | 30.0  | 450  | 0.9995          | 0.7292   | 5e-05  |
| 1.0014        | 31.0  | 465  | 0.9907          | 0.7292   | 0.0000 |
| 0.973         | 32.0  | 480  | 0.9791          | 0.7292   | 0.0000 |
| 0.9894        | 33.0  | 495  | 0.9643          | 0.7188   | 0.0000 |
| 0.9503        | 34.0  | 510  | 0.9531          | 0.7292   | 0.0000 |
| 0.9382        | 35.0  | 525  | 0.9386          | 0.7188   | 0.0000 |
| 0.9371        | 36.0  | 540  | 0.9313          | 0.7188   | 4e-05  |
| 0.9207        | 37.0  | 555  | 0.9192          | 0.7188   | 0.0000 |
| 0.9422        | 38.0  | 570  | 0.9091          | 0.7292   | 0.0000 |
| 0.9041        | 39.0  | 585  | 0.8975          | 0.7188   | 0.0000 |
| 0.8966        | 40.0  | 600  | 0.8888          | 0.7188   | 0.0000 |
| 0.8877        | 41.0  | 615  | 0.8800          | 0.75     | 0.0000 |
| 0.8933        | 42.0  | 630  | 0.8748          | 0.7396   | 3e-05  |
| 0.854         | 43.0  | 645  | 0.8629          | 0.75     | 0.0000 |
| 0.8858        | 44.0  | 660  | 0.8580          | 0.7396   | 0.0000 |
| 0.8407        | 45.0  | 675  | 0.8516          | 0.75     | 0.0000 |
| 0.8413        | 46.0  | 690  | 0.8475          | 0.75     | 0.0000 |
| 0.86          | 47.0  | 705  | 0.8416          | 0.7396   | 0.0000 |
| 0.8282        | 48.0  | 720  | 0.8332          | 0.7396   | 2e-05  |
| 0.835         | 49.0  | 735  | 0.8303          | 0.7396   | 0.0000 |
| 0.8123        | 50.0  | 750  | 0.8267          | 0.7396   | 0.0000 |
| 0.8175        | 51.0  | 765  | 0.8227          | 0.7396   | 0.0000 |
| 0.8097        | 52.0  | 780  | 0.8177          | 0.75     | 0.0000 |
| 0.806         | 53.0  | 795  | 0.8155          | 0.7396   | 0.0000 |


### 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_classifier-only_fr_V2", "results": []}]}
transformers pytorch camembert text-classification generated_from_trainer base_model:camembert/camembert-base-ccnet autotrain_compatible endpoints_compatible region:us