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wav2vec2-large-960h-lv60-self-intent-classification-ori
This model is a fine-tuned version of facebook/wav2vec2-large-960h-lv60-self on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1985
- Accuracy: 0.5417
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2033 | 1.0 | 14 | 2.2126 | 0.0833 |
| 2.2006 | 2.0 | 28 | 2.2026 | 0.0833 |
| 2.1786 | 3.0 | 42 | 2.1758 | 0.3333 |
| 2.1712 | 4.0 | 56 | 2.1436 | 0.3333 |
| 2.1495 | 5.0 | 70 | 2.1120 | 0.3333 |
| 2.1326 | 6.0 | 84 | 2.0909 | 0.3333 |
| 2.1039 | 7.0 | 98 | 2.0966 | 0.3333 |
| 2.0931 | 8.0 | 112 | 2.0355 | 0.3333 |
| 2.1144 | 9.0 | 126 | 2.0082 | 0.3333 |
| 2.0258 | 10.0 | 140 | 1.9901 | 0.375 |
| 2.0028 | 11.0 | 154 | 1.9429 | 0.3958 |
| 1.9737 | 12.0 | 168 | 1.9538 | 0.3958 |
| 1.9023 | 13.0 | 182 | 1.8824 | 0.375 |
| 1.9226 | 14.0 | 196 | 1.8607 | 0.3958 |
| 1.8521 | 15.0 | 210 | 1.8065 | 0.3958 |
| 1.7752 | 16.0 | 224 | 1.8153 | 0.4167 |
| 1.8391 | 17.0 | 238 | 1.7470 | 0.4375 |
| 1.7041 | 18.0 | 252 | 1.7419 | 0.4167 |
| 1.7075 | 19.0 | 266 | 1.6644 | 0.4375 |
| 1.6845 | 20.0 | 280 | 1.6340 | 0.4375 |
| 1.6275 | 21.0 | 294 | 1.6271 | 0.4167 |
| 1.4586 | 22.0 | 308 | 1.5640 | 0.4375 |
| 1.4987 | 23.0 | 322 | 1.5279 | 0.4583 |
| 1.5513 | 24.0 | 336 | 1.4873 | 0.4792 |
| 1.4828 | 25.0 | 350 | 1.4887 | 0.4583 |
| 1.4711 | 26.0 | 364 | 1.4613 | 0.4583 |
| 1.371 | 27.0 | 378 | 1.4062 | 0.4792 |
| 1.3789 | 28.0 | 392 | 1.4038 | 0.4792 |
| 1.3579 | 29.0 | 406 | 1.4031 | 0.4792 |
| 1.2771 | 30.0 | 420 | 1.3637 | 0.5 |
| 1.3417 | 31.0 | 434 | 1.3655 | 0.5 |
| 1.231 | 32.0 | 448 | 1.3698 | 0.5 |
| 1.2367 | 33.0 | 462 | 1.3394 | 0.5 |
| 1.2933 | 34.0 | 476 | 1.3448 | 0.4792 |
| 1.1631 | 35.0 | 490 | 1.2867 | 0.5417 |
| 1.165 | 36.0 | 504 | 1.2624 | 0.5417 |
| 1.2431 | 37.0 | 518 | 1.2252 | 0.5625 |
| 1.1731 | 38.0 | 532 | 1.2082 | 0.5625 |
| 1.1734 | 39.0 | 546 | 1.2062 | 0.5417 |
| 1.1631 | 40.0 | 560 | 1.2034 | 0.5417 |
| 1.0963 | 41.0 | 574 | 1.1973 | 0.5417 |
| 1.2157 | 42.0 | 588 | 1.1988 | 0.5625 |
| 1.1467 | 43.0 | 602 | 1.2018 | 0.5417 |
| 1.1503 | 44.0 | 616 | 1.1986 | 0.5417 |
| 1.0945 | 45.0 | 630 | 1.1985 | 0.5417 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
