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---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_classifier-only_fr_lr1e-3_V3
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. -->
# camembert_ccnet_classification_tools_classifier-only_fr_lr1e-3_V3
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: 0.1260
- Accuracy: 0.9524
- 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.7785 | 1.0 | 14 | 1.5198 | 0.4643 | 0.0010 |
| 1.3586 | 2.0 | 28 | 1.0475 | 0.7381 | 0.0010 |
| 1.0682 | 3.0 | 42 | 0.7517 | 0.7976 | 0.0009 |
| 0.7986 | 4.0 | 56 | 0.7405 | 0.7262 | 0.0009 |
| 0.6711 | 5.0 | 70 | 0.6039 | 0.7976 | 0.0009 |
| 0.6062 | 6.0 | 84 | 0.4750 | 0.8333 | 0.0009 |
| 0.5263 | 7.0 | 98 | 0.3627 | 0.8929 | 0.0009 |
| 0.4188 | 8.0 | 112 | 0.3923 | 0.8452 | 0.0009 |
| 0.4206 | 9.0 | 126 | 0.3147 | 0.9048 | 0.0008 |
| 0.5178 | 10.0 | 140 | 0.3345 | 0.8571 | 0.0008 |
| 0.3435 | 11.0 | 154 | 0.3869 | 0.8095 | 0.0008 |
| 0.3486 | 12.0 | 168 | 0.2324 | 0.9405 | 0.0008 |
| 0.3507 | 13.0 | 182 | 0.2324 | 0.9286 | 0.0008 |
| 0.379 | 14.0 | 196 | 0.2336 | 0.9048 | 0.0008 |
| 0.3516 | 15.0 | 210 | 0.3526 | 0.8571 | 0.0008 |
| 0.3349 | 16.0 | 224 | 0.2204 | 0.9286 | 0.0007 |
| 0.2979 | 17.0 | 238 | 0.2769 | 0.9167 | 0.0007 |
| 0.2981 | 18.0 | 252 | 0.2374 | 0.9048 | 0.0007 |
| 0.2902 | 19.0 | 266 | 0.2410 | 0.9405 | 0.0007 |
| 0.3779 | 20.0 | 280 | 0.2106 | 0.9167 | 0.0007 |
| 0.2486 | 21.0 | 294 | 0.2172 | 0.9405 | 0.0007 |
| 0.2773 | 22.0 | 308 | 0.1927 | 0.9286 | 0.0006 |
| 0.2685 | 23.0 | 322 | 0.1876 | 0.9524 | 0.0006 |
| 0.2416 | 24.0 | 336 | 0.1924 | 0.9286 | 0.0006 |
| 0.2369 | 25.0 | 350 | 0.1686 | 0.9405 | 0.0006 |
| 0.2334 | 26.0 | 364 | 0.2043 | 0.9048 | 0.0006 |
| 0.223 | 27.0 | 378 | 0.1836 | 0.9405 | 0.0006 |
| 0.3389 | 28.0 | 392 | 0.2298 | 0.9167 | 0.0005 |
| 0.2863 | 29.0 | 406 | 0.2005 | 0.9167 | 0.0005 |
| 0.2573 | 30.0 | 420 | 0.1696 | 0.9405 | 0.0005 |
| 0.2192 | 31.0 | 434 | 0.1853 | 0.9286 | 0.0005 |
| 0.2388 | 32.0 | 448 | 0.1546 | 0.9286 | 0.0005 |
| 0.2461 | 33.0 | 462 | 0.1649 | 0.9286 | 0.0005 |
| 0.303 | 34.0 | 476 | 0.1588 | 0.9405 | 0.0004 |
| 0.2262 | 35.0 | 490 | 0.1524 | 0.9405 | 0.0004 |
| 0.3037 | 36.0 | 504 | 0.1469 | 0.9405 | 0.0004 |
| 0.2268 | 37.0 | 518 | 0.1387 | 0.9524 | 0.0004 |
| 0.2315 | 38.0 | 532 | 0.1896 | 0.9405 | 0.0004 |
| 0.2247 | 39.0 | 546 | 0.1572 | 0.9524 | 0.0003 |
| 0.1841 | 40.0 | 560 | 0.1512 | 0.9524 | 0.0003 |
| 0.2357 | 41.0 | 574 | 0.1501 | 0.9405 | 0.0003 |
| 0.2186 | 42.0 | 588 | 0.1642 | 0.9286 | 0.0003 |
| 0.2437 | 43.0 | 602 | 0.1438 | 0.9405 | 0.0003 |
| 0.2399 | 44.0 | 616 | 0.1835 | 0.9405 | 0.0003 |
| 0.2589 | 45.0 | 630 | 0.1565 | 0.9524 | 0.0003 |
| 0.2306 | 46.0 | 644 | 0.1868 | 0.9286 | 0.0002 |
| 0.2159 | 47.0 | 658 | 0.1369 | 0.9524 | 0.0002 |
| 0.212 | 48.0 | 672 | 0.1238 | 0.9524 | 0.0002 |
| 0.1755 | 49.0 | 686 | 0.1439 | 0.9524 | 0.0002 |
| 0.2242 | 50.0 | 700 | 0.1324 | 0.9524 | 0.0002 |
| 0.2211 | 51.0 | 714 | 0.1277 | 0.9524 | 0.0001 |
| 0.1589 | 52.0 | 728 | 0.1268 | 0.9405 | 0.0001 |
| 0.2339 | 53.0 | 742 | 0.1248 | 0.9524 | 0.0001 |
| 0.1963 | 54.0 | 756 | 0.1332 | 0.9524 | 0.0001 |
| 0.2195 | 55.0 | 770 | 0.1350 | 0.9524 | 0.0001 |
| 0.1619 | 56.0 | 784 | 0.1246 | 0.9524 | 0.0001 |
| 0.2054 | 57.0 | 798 | 0.1282 | 0.9524 | 5e-05 |
| 0.206 | 58.0 | 812 | 0.1243 | 0.9524 | 0.0000 |
| 0.188 | 59.0 | 826 | 0.1260 | 0.9524 | 0.0000 |
| 0.1891 | 60.0 | 840 | 0.1260 | 0.9524 | 0.0 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
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