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# camembert_ccnet_classification_tools_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: 0.3572
- Accuracy: 0.9479
- 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.7727        | 1.0   | 15   | 1.2524          | 0.7708   | 0.0001 |
| 0.9027        | 2.0   | 30   | 0.6733          | 0.8646   | 0.0001 |
| 0.4256        | 3.0   | 45   | 0.4453          | 0.8646   | 0.0001 |
| 0.2468        | 4.0   | 60   | 0.2961          | 0.9375   | 0.0001 |
| 0.1407        | 5.0   | 75   | 0.2918          | 0.9271   | 0.0001 |
| 0.082         | 6.0   | 90   | 0.3904          | 0.9062   | 9e-05  |
| 0.0486        | 7.0   | 105  | 0.2854          | 0.9479   | 0.0001 |
| 0.0821        | 8.0   | 120  | 0.2282          | 0.9479   | 0.0001 |
| 0.044         | 9.0   | 135  | 0.2699          | 0.9375   | 0.0001 |
| 0.0308        | 10.0  | 150  | 0.2305          | 0.9479   | 0.0001 |
| 0.0201        | 11.0  | 165  | 0.3650          | 0.9271   | 0.0001 |
| 0.0106        | 12.0  | 180  | 0.3281          | 0.9479   | 8e-05  |
| 0.0079        | 13.0  | 195  | 0.3435          | 0.9479   | 0.0001 |
| 0.007         | 14.0  | 210  | 0.3455          | 0.9479   | 0.0001 |
| 0.0322        | 15.0  | 225  | 0.2507          | 0.9583   | 0.0001 |
| 0.0055        | 16.0  | 240  | 0.2874          | 0.9583   | 0.0001 |
| 0.0047        | 17.0  | 255  | 0.2885          | 0.9583   | 0.0001 |
| 0.0042        | 18.0  | 270  | 0.2875          | 0.9583   | 7e-05  |
| 0.0039        | 19.0  | 285  | 0.2922          | 0.9583   | 0.0001 |
| 0.0035        | 20.0  | 300  | 0.2968          | 0.9583   | 0.0001 |
| 0.0033        | 21.0  | 315  | 0.3038          | 0.9479   | 0.0001 |
| 0.0031        | 22.0  | 330  | 0.3108          | 0.9479   | 0.0001 |
| 0.0029        | 23.0  | 345  | 0.3141          | 0.9479   | 0.0001 |
| 0.0027        | 24.0  | 360  | 0.3151          | 0.9479   | 6e-05  |
| 0.0025        | 25.0  | 375  | 0.3170          | 0.9479   | 0.0001 |
| 0.0023        | 26.0  | 390  | 0.3186          | 0.9479   | 0.0001 |
| 0.0023        | 27.0  | 405  | 0.3194          | 0.9479   | 0.0001 |
| 0.0022        | 28.0  | 420  | 0.3213          | 0.9479   | 0.0001 |
| 0.0021        | 29.0  | 435  | 0.3238          | 0.9479   | 0.0001 |
| 0.002         | 30.0  | 450  | 0.3246          | 0.9479   | 5e-05  |
| 0.0019        | 31.0  | 465  | 0.3273          | 0.9479   | 0.0000 |
| 0.0018        | 32.0  | 480  | 0.3284          | 0.9479   | 0.0000 |
| 0.0017        | 33.0  | 495  | 0.3383          | 0.9479   | 0.0000 |
| 0.0017        | 34.0  | 510  | 0.3408          | 0.9479   | 0.0000 |
| 0.0017        | 35.0  | 525  | 0.3423          | 0.9479   | 0.0000 |
| 0.0016        | 36.0  | 540  | 0.3436          | 0.9479   | 4e-05  |
| 0.0015        | 37.0  | 555  | 0.3451          | 0.9479   | 0.0000 |
| 0.0015        | 38.0  | 570  | 0.3459          | 0.9479   | 0.0000 |
| 0.0014        | 39.0  | 585  | 0.3467          | 0.9479   | 0.0000 |
| 0.0014        | 40.0  | 600  | 0.3479          | 0.9479   | 0.0000 |
| 0.0013        | 41.0  | 615  | 0.3488          | 0.9479   | 0.0000 |
| 0.0013        | 42.0  | 630  | 0.3502          | 0.9479   | 3e-05  |
| 0.0013        | 43.0  | 645  | 0.3501          | 0.9479   | 0.0000 |
| 0.0013        | 44.0  | 660  | 0.3499          | 0.9479   | 0.0000 |
| 0.0012        | 45.0  | 675  | 0.3506          | 0.9479   | 0.0000 |
| 0.0012        | 46.0  | 690  | 0.3515          | 0.9479   | 0.0000 |
| 0.0012        | 47.0  | 705  | 0.3522          | 0.9479   | 0.0000 |
| 0.0012        | 48.0  | 720  | 0.3528          | 0.9479   | 2e-05  |
| 0.0011        | 49.0  | 735  | 0.3534          | 0.9479   | 0.0000 |
| 0.0012        | 50.0  | 750  | 0.3541          | 0.9479   | 0.0000 |
| 0.0011        | 51.0  | 765  | 0.3545          | 0.9479   | 0.0000 |
| 0.0011        | 52.0  | 780  | 0.3549          | 0.9479   | 0.0000 |
| 0.0011        | 53.0  | 795  | 0.3556          | 0.9479   | 0.0000 |
| 0.0011        | 54.0  | 810  | 0.3560          | 0.9479   | 1e-05  |
| 0.0011        | 55.0  | 825  | 0.3563          | 0.9479   | 0.0000 |
| 0.0011        | 56.0  | 840  | 0.3567          | 0.9479   | 0.0000 |
| 0.0011        | 57.0  | 855  | 0.3570          | 0.9479   | 5e-06  |
| 0.0011        | 58.0  | 870  | 0.3571          | 0.9479   | 0.0000 |
| 0.0011        | 59.0  | 885  | 0.3572          | 0.9479   | 0.0000 |
| 0.001         | 60.0  | 900  | 0.3572          | 0.9479   | 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_fr_V2", "results": []}]}
transformers pytorch camembert text-classification generated_from_trainer base_model:camembert/camembert-base-ccnet autotrain_compatible endpoints_compatible region:us