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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
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
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: 0.2297
- Accuracy: 0.975
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 7 | 1.7771 | 0.5 | 0.0010 |
| No log | 2.0 | 14 | 1.5458 | 0.425 | 0.0010 |
| No log | 3.0 | 21 | 1.2091 | 0.75 | 0.0009 |
| No log | 4.0 | 28 | 1.0227 | 0.75 | 0.0009 |
| No log | 5.0 | 35 | 0.9105 | 0.7 | 0.0009 |
| No log | 6.0 | 42 | 0.7765 | 0.825 | 0.0009 |
| No log | 7.0 | 49 | 0.7397 | 0.75 | 0.0009 |
| No log | 8.0 | 56 | 0.6652 | 0.825 | 0.0009 |
| No log | 9.0 | 63 | 0.6385 | 0.775 | 0.0008 |
| No log | 10.0 | 70 | 0.6051 | 0.8 | 0.0008 |
| No log | 11.0 | 77 | 0.5246 | 0.9 | 0.0008 |
| No log | 12.0 | 84 | 0.5391 | 0.825 | 0.0008 |
| No log | 13.0 | 91 | 0.5511 | 0.825 | 0.0008 |
| No log | 14.0 | 98 | 0.4780 | 0.85 | 0.0008 |
| No log | 15.0 | 105 | 0.4328 | 0.925 | 0.0008 |
| No log | 16.0 | 112 | 0.4016 | 0.875 | 0.0007 |
| No log | 17.0 | 119 | 0.4902 | 0.8 | 0.0007 |
| No log | 18.0 | 126 | 0.4016 | 0.9 | 0.0007 |
| No log | 19.0 | 133 | 0.4164 | 0.9 | 0.0007 |
| No log | 20.0 | 140 | 0.3814 | 0.825 | 0.0007 |
| No log | 21.0 | 147 | 0.3147 | 0.95 | 0.0007 |
| No log | 22.0 | 154 | 0.3544 | 0.9 | 0.0006 |
| No log | 23.0 | 161 | 0.3438 | 0.9 | 0.0006 |
| No log | 24.0 | 168 | 0.3181 | 0.95 | 0.0006 |
| No log | 25.0 | 175 | 0.3433 | 0.875 | 0.0006 |
| No log | 26.0 | 182 | 0.3197 | 0.95 | 0.0006 |
| No log | 27.0 | 189 | 0.3510 | 0.875 | 0.0006 |
| No log | 28.0 | 196 | 0.3495 | 0.9 | 0.0005 |
| No log | 29.0 | 203 | 0.2704 | 0.95 | 0.0005 |
| No log | 30.0 | 210 | 0.3081 | 0.975 | 0.0005 |
| No log | 31.0 | 217 | 0.3389 | 0.875 | 0.0005 |
| No log | 32.0 | 224 | 0.2695 | 0.95 | 0.0005 |
| No log | 33.0 | 231 | 0.2903 | 0.925 | 0.0005 |
| No log | 34.0 | 238 | 0.3012 | 0.925 | 0.0004 |
| No log | 35.0 | 245 | 0.2804 | 0.95 | 0.0004 |
| No log | 36.0 | 252 | 0.2716 | 0.95 | 0.0004 |
| No log | 37.0 | 259 | 0.3125 | 0.875 | 0.0004 |
| No log | 38.0 | 266 | 0.2501 | 0.925 | 0.0004 |
| No log | 39.0 | 273 | 0.2442 | 0.95 | 0.0003 |
| No log | 40.0 | 280 | 0.2284 | 0.95 | 0.0003 |
| No log | 41.0 | 287 | 0.2363 | 0.975 | 0.0003 |
| No log | 42.0 | 294 | 0.2656 | 0.975 | 0.0003 |
| No log | 43.0 | 301 | 0.2723 | 0.925 | 0.0003 |
| No log | 44.0 | 308 | 0.2302 | 0.95 | 0.0003 |
| No log | 45.0 | 315 | 0.2391 | 0.95 | 0.0003 |
| No log | 46.0 | 322 | 0.2414 | 0.95 | 0.0002 |
| No log | 47.0 | 329 | 0.2506 | 0.975 | 0.0002 |
| No log | 48.0 | 336 | 0.2616 | 0.975 | 0.0002 |
| No log | 49.0 | 343 | 0.2376 | 0.975 | 0.0002 |
| No log | 50.0 | 350 | 0.2310 | 0.975 | 0.0002 |
| No log | 51.0 | 357 | 0.2271 | 0.95 | 0.0001 |
| No log | 52.0 | 364 | 0.2484 | 0.95 | 0.0001 |
| No log | 53.0 | 371 | 0.2633 | 0.95 | 0.0001 |
| No log | 54.0 | 378 | 0.2788 | 0.925 | 0.0001 |
| No log | 55.0 | 385 | 0.2626 | 0.975 | 0.0001 |
| No log | 56.0 | 392 | 0.2454 | 0.975 | 0.0001 |
| No log | 57.0 | 399 | 0.2373 | 0.975 | 5e-05 |
| No log | 58.0 | 406 | 0.2340 | 0.975 | 0.0000 |
| No log | 59.0 | 413 | 0.2291 | 0.975 | 0.0000 |
| No log | 60.0 | 420 | 0.2297 | 0.975 | 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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