MiniLM_classification_tools_qlora_fr
This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0142
- Accuracy: 0.35
- 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 |
|---|---|---|---|---|---|
| No log | 1.0 | 7 | 2.0827 | 0.075 | 0.0001 |
| No log | 2.0 | 14 | 2.0846 | 0.075 | 0.0001 |
| No log | 3.0 | 21 | 2.0865 | 0.075 | 0.0001 |
| No log | 4.0 | 28 | 2.0880 | 0.075 | 0.0001 |
| No log | 5.0 | 35 | 2.0896 | 0.075 | 0.0001 |
| No log | 6.0 | 42 | 2.0914 | 0.075 | 9e-05 |
| No log | 7.0 | 49 | 2.0935 | 0.075 | 0.0001 |
| No log | 8.0 | 56 | 2.0953 | 0.075 | 0.0001 |
| No log | 9.0 | 63 | 2.0973 | 0.075 | 0.0001 |
| No log | 10.0 | 70 | 2.0997 | 0.075 | 0.0001 |
| No log | 11.0 | 77 | 2.1013 | 0.075 | 0.0001 |
| No log | 12.0 | 84 | 2.1032 | 0.075 | 8e-05 |
| No log | 13.0 | 91 | 2.1044 | 0.075 | 0.0001 |
| No log | 14.0 | 98 | 2.1061 | 0.075 | 0.0001 |
| No log | 15.0 | 105 | 2.1071 | 0.075 | 0.0001 |
| No log | 16.0 | 112 | 2.1084 | 0.075 | 0.0001 |
| No log | 17.0 | 119 | 2.1097 | 0.075 | 0.0001 |
| No log | 18.0 | 126 | 2.1111 | 0.1 | 7e-05 |
| No log | 19.0 | 133 | 2.1126 | 0.15 | 0.0001 |
| No log | 20.0 | 140 | 2.1141 | 0.15 | 0.0001 |
| No log | 21.0 | 147 | 2.1155 | 0.15 | 0.0001 |
| No log | 22.0 | 154 | 2.1163 | 0.15 | 0.0001 |
| No log | 23.0 | 161 | 2.1175 | 0.15 | 0.0001 |
| No log | 24.0 | 168 | 2.1181 | 0.15 | 6e-05 |
| No log | 25.0 | 175 | 2.1183 | 0.15 | 0.0001 |
| No log | 26.0 | 182 | 2.1186 | 0.15 | 0.0001 |
| No log | 27.0 | 189 | 2.1182 | 0.15 | 0.0001 |
| No log | 28.0 | 196 | 2.1166 | 0.15 | 0.0001 |
| No log | 29.0 | 203 | 2.1150 | 0.15 | 0.0001 |
| No log | 30.0 | 210 | 2.1119 | 0.15 | 5e-05 |
| No log | 31.0 | 217 | 2.1078 | 0.15 | 0.0000 |
| No log | 32.0 | 224 | 2.1041 | 0.15 | 0.0000 |
| No log | 33.0 | 231 | 2.1003 | 0.15 | 0.0000 |
| No log | 34.0 | 238 | 2.0975 | 0.15 | 0.0000 |
| No log | 35.0 | 245 | 2.0937 | 0.15 | 0.0000 |
| No log | 36.0 | 252 | 2.0903 | 0.15 | 4e-05 |
| No log | 37.0 | 259 | 2.0857 | 0.15 | 0.0000 |
| No log | 38.0 | 266 | 2.0795 | 0.15 | 0.0000 |
| No log | 39.0 | 273 | 2.0746 | 0.175 | 0.0000 |
| No log | 40.0 | 280 | 2.0709 | 0.225 | 0.0000 |
| No log | 41.0 | 287 | 2.0656 | 0.275 | 0.0000 |
| No log | 42.0 | 294 | 2.0597 | 0.225 | 3e-05 |
| No log | 43.0 | 301 | 2.0553 | 0.275 | 0.0000 |
| No log | 44.0 | 308 | 2.0508 | 0.275 | 0.0000 |
| No log | 45.0 | 315 | 2.0451 | 0.3 | 0.0000 |
| No log | 46.0 | 322 | 2.0408 | 0.3 | 0.0000 |
| No log | 47.0 | 329 | 2.0393 | 0.325 | 0.0000 |
| No log | 48.0 | 336 | 2.0368 | 0.35 | 2e-05 |
| No log | 49.0 | 343 | 2.0318 | 0.35 | 0.0000 |
| No log | 50.0 | 350 | 2.0282 | 0.35 | 0.0000 |
| No log | 51.0 | 357 | 2.0268 | 0.35 | 0.0000 |
| No log | 52.0 | 364 | 2.0247 | 0.35 | 0.0000 |
| No log | 53.0 | 371 | 2.0216 | 0.35 | 0.0000 |
| No log | 54.0 | 378 | 2.0195 | 0.35 | 1e-05 |
| No log | 55.0 | 385 | 2.0182 | 0.35 | 0.0000 |
| No log | 56.0 | 392 | 2.0172 | 0.35 | 0.0000 |
| No log | 57.0 | 399 | 2.0159 | 0.35 | 5e-06 |
| No log | 58.0 | 406 | 2.0148 | 0.35 | 0.0000 |
| No log | 59.0 | 413 | 2.0143 | 0.35 | 0.0000 |
| No log | 60.0 | 420 | 2.0142 | 0.35 | 0.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1