wav2vec2-xlsr-53-espeak-cv-ft-intent-classification-ori
This model is a fine-tuned version of facebook/wav2vec2-xlsr-53-espeak-cv-ft on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9124
- Accuracy: 0.625
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 |
|---|---|---|---|---|
| 2.1894 | 1.0 | 14 | 2.1812 | 0.3333 |
| 2.1795 | 2.0 | 28 | 2.1553 | 0.3333 |
| 2.144 | 3.0 | 42 | 2.1066 | 0.3333 |
| 2.1175 | 4.0 | 56 | 2.0283 | 0.3542 |
| 2.0542 | 5.0 | 70 | 1.9253 | 0.3958 |
| 2.0007 | 6.0 | 84 | 1.8468 | 0.4167 |
| 1.8891 | 7.0 | 98 | 1.7655 | 0.4583 |
| 1.8484 | 8.0 | 112 | 1.6695 | 0.4792 |
| 1.8256 | 9.0 | 126 | 1.5920 | 0.5 |
| 1.6832 | 10.0 | 140 | 1.5331 | 0.5 |
| 1.6149 | 11.0 | 154 | 1.4763 | 0.5 |
| 1.5853 | 12.0 | 168 | 1.4453 | 0.5 |
| 1.4357 | 13.0 | 182 | 1.3588 | 0.5 |
| 1.4789 | 14.0 | 196 | 1.3238 | 0.4792 |
| 1.3886 | 15.0 | 210 | 1.2822 | 0.4792 |
| 1.313 | 16.0 | 224 | 1.2609 | 0.5 |
| 1.3559 | 17.0 | 238 | 1.2191 | 0.5208 |
| 1.1937 | 18.0 | 252 | 1.1936 | 0.5 |
| 1.1847 | 19.0 | 266 | 1.1547 | 0.5417 |
| 1.197 | 20.0 | 280 | 1.1390 | 0.5417 |
| 1.1057 | 21.0 | 294 | 1.1310 | 0.5208 |
| 1.0291 | 22.0 | 308 | 1.1086 | 0.5417 |
| 1.0768 | 23.0 | 322 | 1.1075 | 0.5417 |
| 1.0249 | 24.0 | 336 | 1.0654 | 0.5625 |
| 1.0433 | 25.0 | 350 | 1.0390 | 0.5625 |
| 0.9974 | 26.0 | 364 | 1.0086 | 0.6458 |
| 0.9578 | 27.0 | 378 | 0.9939 | 0.625 |
| 0.916 | 28.0 | 392 | 0.9938 | 0.625 |
| 0.9187 | 29.0 | 406 | 0.9843 | 0.625 |
| 0.8759 | 30.0 | 420 | 0.9755 | 0.625 |
| 0.9199 | 31.0 | 434 | 0.9822 | 0.6042 |
| 0.8791 | 32.0 | 448 | 0.9522 | 0.6458 |
| 0.8436 | 33.0 | 462 | 0.9414 | 0.6458 |
| 0.8692 | 34.0 | 476 | 0.9510 | 0.625 |
| 0.8201 | 35.0 | 490 | 0.9208 | 0.6667 |
| 0.8284 | 36.0 | 504 | 0.9398 | 0.6458 |
| 0.8761 | 37.0 | 518 | 0.9438 | 0.6458 |
| 0.7948 | 38.0 | 532 | 0.9253 | 0.6667 |
| 0.8339 | 39.0 | 546 | 0.9250 | 0.6458 |
| 0.8002 | 40.0 | 560 | 0.9145 | 0.6458 |
| 0.7791 | 41.0 | 574 | 0.9062 | 0.6667 |
| 0.7944 | 42.0 | 588 | 0.9077 | 0.6667 |
| 0.7777 | 43.0 | 602 | 0.9069 | 0.6458 |
| 0.7943 | 44.0 | 616 | 0.9118 | 0.625 |
| 0.7573 | 45.0 | 630 | 0.9124 | 0.625 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1