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wav2vec2-large-xlsr-53-intent-classification-ori
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7682
- Accuracy: 0.4167
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 |
|---|---|---|---|---|
| 2.2017 | 1.0 | 14 | 2.2113 | 0.1042 |
| 2.2013 | 2.0 | 28 | 2.2078 | 0.0625 |
| 2.197 | 3.0 | 42 | 2.1981 | 0.0625 |
| 2.1917 | 4.0 | 56 | 2.1760 | 0.3125 |
| 2.1759 | 5.0 | 70 | 2.1534 | 0.3333 |
| 2.1713 | 6.0 | 84 | 2.1305 | 0.3333 |
| 2.1431 | 7.0 | 98 | 2.1044 | 0.3333 |
| 2.1366 | 8.0 | 112 | 2.0838 | 0.3333 |
| 2.1482 | 9.0 | 126 | 2.0649 | 0.3333 |
| 2.1074 | 10.0 | 140 | 2.0532 | 0.3333 |
| 2.1066 | 11.0 | 154 | 2.0506 | 0.3333 |
| 2.089 | 12.0 | 168 | 2.0624 | 0.3333 |
| 2.0625 | 13.0 | 182 | 2.0580 | 0.3333 |
| 2.1106 | 14.0 | 196 | 2.0419 | 0.3333 |
| 2.0714 | 15.0 | 210 | 2.0350 | 0.3333 |
| 2.0256 | 16.0 | 224 | 2.0333 | 0.3333 |
| 2.1226 | 17.0 | 238 | 2.0286 | 0.3333 |
| 2.0451 | 18.0 | 252 | 2.0195 | 0.3333 |
| 2.0822 | 19.0 | 266 | 1.9968 | 0.3333 |
| 2.0991 | 20.0 | 280 | 1.9883 | 0.3333 |
| 2.0537 | 21.0 | 294 | 1.9767 | 0.3333 |
| 1.973 | 22.0 | 308 | 1.9524 | 0.3333 |
| 2.0429 | 23.0 | 322 | 1.9432 | 0.3333 |
| 2.0091 | 24.0 | 336 | 1.9402 | 0.3333 |
| 2.0309 | 25.0 | 350 | 1.9295 | 0.3333 |
| 2.0261 | 26.0 | 364 | 1.9167 | 0.3333 |
| 2.0081 | 27.0 | 378 | 1.9083 | 0.3333 |
| 2.023 | 28.0 | 392 | 1.9013 | 0.3333 |
| 2.0 | 29.0 | 406 | 1.8623 | 0.375 |
| 1.936 | 30.0 | 420 | 1.8483 | 0.3958 |
| 1.9809 | 31.0 | 434 | 1.8344 | 0.3958 |
| 1.9645 | 32.0 | 448 | 1.8428 | 0.4167 |
| 1.9788 | 33.0 | 462 | 1.8372 | 0.3958 |
| 1.9484 | 34.0 | 476 | 1.8246 | 0.3958 |
| 1.9553 | 35.0 | 490 | 1.7941 | 0.4167 |
| 1.9321 | 36.0 | 504 | 1.7824 | 0.4167 |
| 1.9759 | 37.0 | 518 | 1.7884 | 0.3958 |
| 1.9424 | 38.0 | 532 | 1.7875 | 0.3958 |
| 1.9592 | 39.0 | 546 | 1.7901 | 0.3958 |
| 1.9425 | 40.0 | 560 | 1.7812 | 0.3958 |
| 1.8899 | 41.0 | 574 | 1.7736 | 0.3958 |
| 1.9361 | 42.0 | 588 | 1.7711 | 0.4167 |
| 1.9023 | 43.0 | 602 | 1.7711 | 0.4167 |
| 1.9203 | 44.0 | 616 | 1.7688 | 0.4167 |
| 1.8921 | 45.0 | 630 | 1.7682 | 0.4167 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
