metadata
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_qlora-8bit_fr
results: []
camembert_ccnet_classification_tools_qlora-8bit_fr
This model is a fine-tuned version of camembert/camembert-base-ccnet on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5066
- Accuracy: 0.85
- 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 |
|---|---|---|---|---|---|
| 2.0629 | 1.0 | 7 | 2.0715 | 0.125 | 0.0001 |
| 2.0638 | 2.0 | 14 | 2.0676 | 0.15 | 0.0001 |
| 2.0614 | 3.0 | 21 | 2.0661 | 0.1 | 0.0001 |
| 2.0676 | 4.0 | 28 | 2.0622 | 0.125 | 0.0001 |
| 2.0502 | 5.0 | 35 | 2.0530 | 0.15 | 0.0001 |
| 2.0409 | 6.0 | 42 | 2.0480 | 0.175 | 9e-05 |
| 2.0457 | 7.0 | 49 | 2.0431 | 0.1 | 0.0001 |
| 2.0401 | 8.0 | 56 | 2.0398 | 0.125 | 0.0001 |
| 2.0239 | 9.0 | 63 | 2.0283 | 0.275 | 0.0001 |
| 2.0257 | 10.0 | 70 | 2.0131 | 0.3 | 0.0001 |
| 1.999 | 11.0 | 77 | 1.9926 | 0.425 | 0.0001 |
| 2.0053 | 12.0 | 84 | 1.9866 | 0.4 | 8e-05 |
| 1.9893 | 13.0 | 91 | 1.9710 | 0.475 | 0.0001 |
| 1.9762 | 14.0 | 98 | 1.9572 | 0.475 | 0.0001 |
| 1.9726 | 15.0 | 105 | 1.9398 | 0.425 | 0.0001 |
| 1.9456 | 16.0 | 112 | 1.9152 | 0.5 | 0.0001 |
| 1.9425 | 17.0 | 119 | 1.8971 | 0.575 | 0.0001 |
| 1.9078 | 18.0 | 126 | 1.8788 | 0.625 | 7e-05 |
| 1.901 | 19.0 | 133 | 1.8608 | 0.65 | 0.0001 |
| 1.8865 | 20.0 | 140 | 1.8407 | 0.625 | 0.0001 |
| 1.8696 | 21.0 | 147 | 1.8234 | 0.675 | 0.0001 |
| 1.8618 | 22.0 | 154 | 1.7964 | 0.725 | 0.0001 |
| 1.8238 | 23.0 | 161 | 1.7778 | 0.725 | 0.0001 |
| 1.8164 | 24.0 | 168 | 1.7739 | 0.675 | 6e-05 |
| 1.823 | 25.0 | 175 | 1.7442 | 0.675 | 0.0001 |
| 1.7892 | 26.0 | 182 | 1.7265 | 0.7 | 0.0001 |
| 1.7865 | 27.0 | 189 | 1.7110 | 0.75 | 0.0001 |
| 1.7643 | 28.0 | 196 | 1.7114 | 0.725 | 0.0001 |
| 1.7613 | 29.0 | 203 | 1.6859 | 0.775 | 0.0001 |
| 1.7681 | 30.0 | 210 | 1.6686 | 0.775 | 5e-05 |
| 1.7251 | 31.0 | 217 | 1.6547 | 0.8 | 0.0000 |
| 1.7215 | 32.0 | 224 | 1.6431 | 0.8 | 0.0000 |
| 1.7304 | 33.0 | 231 | 1.6285 | 0.75 | 0.0000 |
| 1.7182 | 34.0 | 238 | 1.6164 | 0.8 | 0.0000 |
| 1.7099 | 35.0 | 245 | 1.6066 | 0.825 | 0.0000 |
| 1.6902 | 36.0 | 252 | 1.6060 | 0.8 | 4e-05 |
| 1.6839 | 37.0 | 259 | 1.5949 | 0.875 | 0.0000 |
| 1.6627 | 38.0 | 266 | 1.5822 | 0.875 | 0.0000 |
| 1.6558 | 39.0 | 273 | 1.5723 | 0.875 | 0.0000 |
| 1.6667 | 40.0 | 280 | 1.5639 | 0.85 | 0.0000 |
| 1.6663 | 41.0 | 287 | 1.5576 | 0.85 | 0.0000 |
| 1.642 | 42.0 | 294 | 1.5506 | 0.825 | 3e-05 |
| 1.6479 | 43.0 | 301 | 1.5471 | 0.825 | 0.0000 |
| 1.6425 | 44.0 | 308 | 1.5414 | 0.825 | 0.0000 |
| 1.6214 | 45.0 | 315 | 1.5351 | 0.85 | 0.0000 |
| 1.6331 | 46.0 | 322 | 1.5310 | 0.875 | 0.0000 |
| 1.6406 | 47.0 | 329 | 1.5281 | 0.875 | 0.0000 |
| 1.6332 | 48.0 | 336 | 1.5265 | 0.875 | 2e-05 |
| 1.6474 | 49.0 | 343 | 1.5218 | 0.875 | 0.0000 |
| 1.6122 | 50.0 | 350 | 1.5184 | 0.875 | 0.0000 |
| 1.6166 | 51.0 | 357 | 1.5162 | 0.875 | 0.0000 |
| 1.6245 | 52.0 | 364 | 1.5343 | 0.875 | 0.0000 |
| 1.6027 | 53.0 | 371 | 1.5272 | 0.85 | 0.0000 |
| 1.6305 | 54.0 | 378 | 1.5261 | 0.85 | 1e-05 |
| 1.6172 | 55.0 | 385 | 1.5173 | 0.85 | 0.0000 |
| 1.6109 | 56.0 | 392 | 1.5168 | 0.875 | 0.0000 |
| 1.6037 | 57.0 | 399 | 1.5154 | 0.875 | 5e-06 |
| 1.6031 | 58.0 | 406 | 1.4970 | 0.875 | 0.0000 |
| 1.617 | 59.0 | 413 | 1.4961 | 0.875 | 0.0000 |
| 1.5955 | 60.0 | 420 | 1.5066 | 0.85 | 0.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1