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wav2vec2-large-960h-intent-classification-ori
This model is a fine-tuned version of facebook/wav2vec2-large-960h on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6013
- Accuracy: 0.7708
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 |
|---|---|---|---|---|
| 2.1937 | 1.0 | 14 | 2.1715 | 0.3333 |
| 2.1764 | 2.0 | 28 | 2.1317 | 0.3333 |
| 2.1358 | 3.0 | 42 | 2.0794 | 0.3333 |
| 2.1227 | 4.0 | 56 | 2.0367 | 0.3333 |
| 2.1157 | 5.0 | 70 | 1.9845 | 0.3333 |
| 2.0776 | 6.0 | 84 | 1.9369 | 0.3333 |
| 2.0126 | 7.0 | 98 | 1.8021 | 0.375 |
| 1.88 | 8.0 | 112 | 1.6825 | 0.4167 |
| 1.8818 | 9.0 | 126 | 1.4638 | 0.5 |
| 1.7044 | 10.0 | 140 | 1.4188 | 0.5208 |
| 1.5442 | 11.0 | 154 | 1.3421 | 0.5625 |
| 1.5045 | 12.0 | 168 | 1.3971 | 0.5 |
| 1.3369 | 13.0 | 182 | 1.1602 | 0.5833 |
| 1.4017 | 14.0 | 196 | 1.3510 | 0.5417 |
| 1.2565 | 15.0 | 210 | 1.0978 | 0.5625 |
| 1.1056 | 16.0 | 224 | 1.0847 | 0.5833 |
| 1.2006 | 17.0 | 238 | 1.0262 | 0.625 |
| 0.9235 | 18.0 | 252 | 0.9532 | 0.7083 |
| 0.9528 | 19.0 | 266 | 1.0212 | 0.6042 |
| 0.8195 | 20.0 | 280 | 0.8442 | 0.7083 |
| 0.7518 | 21.0 | 294 | 0.8379 | 0.6875 |
| 0.6017 | 22.0 | 308 | 0.9422 | 0.7292 |
| 0.7697 | 23.0 | 322 | 0.7353 | 0.75 |
| 0.5367 | 24.0 | 336 | 0.8685 | 0.6875 |
| 0.5655 | 25.0 | 350 | 0.7440 | 0.7708 |
| 0.5116 | 26.0 | 364 | 0.7572 | 0.75 |
| 0.4297 | 27.0 | 378 | 0.7518 | 0.75 |
| 0.4928 | 28.0 | 392 | 0.5988 | 0.7917 |
| 0.4424 | 29.0 | 406 | 0.7240 | 0.75 |
| 0.3313 | 30.0 | 420 | 0.6173 | 0.7708 |
| 0.3854 | 31.0 | 434 | 0.7375 | 0.75 |
| 0.4131 | 32.0 | 448 | 0.7026 | 0.7708 |
| 0.2899 | 33.0 | 462 | 0.6516 | 0.7708 |
| 0.3644 | 34.0 | 476 | 0.6201 | 0.7917 |
| 0.2316 | 35.0 | 490 | 0.6111 | 0.7708 |
| 0.2589 | 36.0 | 504 | 0.5518 | 0.7917 |
| 0.3778 | 37.0 | 518 | 0.5512 | 0.7708 |
| 0.2426 | 38.0 | 532 | 0.5779 | 0.7917 |
| 0.304 | 39.0 | 546 | 0.7771 | 0.75 |
| 0.1833 | 40.0 | 560 | 0.5839 | 0.7708 |
| 0.1649 | 41.0 | 574 | 0.5699 | 0.7708 |
| 0.2529 | 42.0 | 588 | 0.6190 | 0.75 |
| 0.2121 | 43.0 | 602 | 0.5992 | 0.75 |
| 0.2736 | 44.0 | 616 | 0.6011 | 0.7917 |
| 0.2446 | 45.0 | 630 | 0.6013 | 0.7708 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
