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wav2vec2-xls-r-300m-arabic_speech_commands_10s_one_speaker_all_classes_3_aug
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1190
- Accuracy: 0.7137
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 60
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.6888 | 0.96 | 12 | 3.6887 | 0.025 |
| 3.8686 | 1.96 | 24 | 3.6837 | 0.0488 |
| 3.844 | 2.96 | 36 | 3.5466 | 0.1062 |
| 3.7114 | 3.96 | 48 | 3.2589 | 0.1133 |
| 2.8339 | 4.96 | 60 | 2.9553 | 0.1883 |
| 2.5667 | 5.96 | 72 | 2.8784 | 0.1963 |
| 2.1911 | 6.96 | 84 | 2.6379 | 0.2771 |
| 1.8461 | 7.96 | 96 | 2.8874 | 0.2929 |
| 1.6044 | 8.96 | 108 | 2.4989 | 0.34 |
| 1.0916 | 9.96 | 120 | 2.3111 | 0.425 |
| 0.9371 | 10.96 | 132 | 2.0899 | 0.4829 |
| 0.8177 | 11.96 | 144 | 2.0116 | 0.4971 |
| 0.6366 | 12.96 | 156 | 2.0598 | 0.5558 |
| 0.549 | 13.96 | 168 | 2.0084 | 0.5575 |
| 0.2917 | 14.96 | 180 | 1.8231 | 0.6038 |
| 0.2283 | 15.96 | 192 | 1.9943 | 0.6079 |
| 0.2382 | 16.96 | 204 | 2.2098 | 0.6083 |
| 0.2475 | 17.96 | 216 | 2.3519 | 0.5992 |
| 0.1612 | 18.96 | 228 | 2.2483 | 0.5929 |
| 0.133 | 19.96 | 240 | 2.2263 | 0.6079 |
| 0.1301 | 20.96 | 252 | 2.6094 | 0.5683 |
| 0.0993 | 21.96 | 264 | 2.0289 | 0.6417 |
| 0.0779 | 22.96 | 276 | 1.9693 | 0.6479 |
| 0.0824 | 23.96 | 288 | 2.2471 | 0.6258 |
| 0.0872 | 24.96 | 300 | 2.3715 | 0.6538 |
| 0.0694 | 25.96 | 312 | 2.5367 | 0.6325 |
| 0.0704 | 26.96 | 324 | 2.4467 | 0.6388 |
| 0.061 | 27.96 | 336 | 2.1581 | 0.6621 |
| 0.0835 | 28.96 | 348 | 2.1672 | 0.6792 |
| 0.0402 | 29.96 | 360 | 2.2166 | 0.6596 |
| 0.0329 | 30.96 | 372 | 2.6316 | 0.6217 |
| 0.0516 | 31.96 | 384 | 2.0840 | 0.6908 |
| 0.0455 | 32.96 | 396 | 2.2299 | 0.67 |
| 0.0449 | 33.96 | 408 | 2.4341 | 0.6733 |
| 0.0332 | 34.96 | 420 | 2.2830 | 0.6725 |
| 0.0334 | 35.96 | 432 | 2.2060 | 0.6829 |
| 0.025 | 36.96 | 444 | 2.2836 | 0.6554 |
| 0.0351 | 37.96 | 456 | 2.5417 | 0.6517 |
| 0.0372 | 38.96 | 468 | 2.2738 | 0.6779 |
| 0.0136 | 39.96 | 480 | 2.4606 | 0.6525 |
| 0.0178 | 40.96 | 492 | 2.1996 | 0.675 |
| 0.0116 | 41.96 | 504 | 2.2557 | 0.6763 |
| 0.0113 | 42.96 | 516 | 2.2061 | 0.6863 |
| 0.014 | 43.96 | 528 | 2.1279 | 0.6925 |
| 0.015 | 44.96 | 540 | 2.2151 | 0.6871 |
| 0.0197 | 45.96 | 552 | 2.1506 | 0.6929 |
| 0.0102 | 46.96 | 564 | 2.1609 | 0.685 |
| 0.0115 | 47.96 | 576 | 2.1685 | 0.6854 |
| 0.0097 | 48.96 | 588 | 2.2892 | 0.6821 |
| 0.0148 | 49.96 | 600 | 2.4085 | 0.6921 |
| 0.0114 | 50.96 | 612 | 2.2171 | 0.7104 |
| 0.0141 | 51.96 | 624 | 2.1458 | 0.7075 |
| 0.0066 | 52.96 | 636 | 2.2046 | 0.7013 |
| 0.0128 | 53.96 | 648 | 2.1424 | 0.705 |
| 0.0063 | 54.96 | 660 | 2.1425 | 0.7075 |
| 0.0094 | 55.96 | 672 | 2.1554 | 0.7087 |
| 0.0161 | 56.96 | 684 | 2.1892 | 0.7063 |
| 0.0067 | 57.96 | 696 | 2.1819 | 0.7067 |
| 0.0099 | 58.96 | 708 | 2.1341 | 0.7125 |
| 0.0067 | 59.96 | 720 | 2.1190 | 0.7137 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
