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---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_NEFTune_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_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
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