wav2vec2-base-intent-classification-ori
This model is a fine-tuned version of facebook/wav2vec2-base on the intent-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4928
- Accuracy: 0.9167
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|---|---|---|---|---|
| 2.1867 | 1.0 | 28 | 2.1745 | 0.2708 |
| 2.1177 | 2.0 | 56 | 2.1165 | 0.2708 |
| 2.1012 | 3.0 | 84 | 2.0553 | 0.2708 |
| 1.9851 | 4.0 | 112 | 1.9551 | 0.375 |
| 1.9092 | 5.0 | 140 | 1.9765 | 0.2917 |
| 1.6848 | 6.0 | 168 | 1.8461 | 0.2917 |
| 1.6576 | 7.0 | 196 | 1.5223 | 0.5 |
| 1.4492 | 8.0 | 224 | 1.4500 | 0.4792 |
| 1.2193 | 9.0 | 252 | 1.5349 | 0.4792 |
| 1.1149 | 10.0 | 280 | 1.2159 | 0.5833 |
| 1.0615 | 11.0 | 308 | 1.1469 | 0.6875 |
| 1.0584 | 12.0 | 336 | 1.2778 | 0.6042 |
| 0.8237 | 13.0 | 364 | 1.1774 | 0.5625 |
| 0.6699 | 14.0 | 392 | 0.9661 | 0.6875 |
| 0.7414 | 15.0 | 420 | 1.2787 | 0.5208 |
| 0.5324 | 16.0 | 448 | 0.8592 | 0.7292 |
| 0.3753 | 17.0 | 476 | 0.6860 | 0.7917 |
| 0.3274 | 18.0 | 504 | 0.6210 | 0.8333 |
| 0.3667 | 19.0 | 532 | 0.7310 | 0.75 |
| 0.2347 | 20.0 | 560 | 0.6801 | 0.7292 |
| 0.2036 | 21.0 | 588 | 0.9876 | 0.6875 |
| 0.1711 | 22.0 | 616 | 0.6323 | 0.7917 |
| 0.205 | 23.0 | 644 | 0.4414 | 0.8958 |
| 0.0892 | 24.0 | 672 | 0.4253 | 0.8958 |
| 0.0777 | 25.0 | 700 | 0.4703 | 0.8958 |
| 0.0717 | 26.0 | 728 | 0.4883 | 0.8958 |
| 0.041 | 27.0 | 756 | 0.6224 | 0.8542 |
| 0.0493 | 28.0 | 784 | 0.5839 | 0.875 |
| 0.0405 | 29.0 | 812 | 0.6454 | 0.8542 |
| 0.04 | 30.0 | 840 | 0.6102 | 0.875 |
| 0.0333 | 31.0 | 868 | 0.6080 | 0.875 |
| 0.0303 | 32.0 | 896 | 0.5539 | 0.875 |
| 0.025 | 33.0 | 924 | 0.5799 | 0.8958 |
| 0.0246 | 34.0 | 952 | 0.5766 | 0.8958 |
| 0.0209 | 35.0 | 980 | 0.5700 | 0.8958 |
| 0.0225 | 36.0 | 1008 | 0.5709 | 0.8958 |
| 0.0225 | 37.0 | 1036 | 0.5582 | 0.8958 |
| 0.0217 | 38.0 | 1064 | 0.5258 | 0.875 |
| 0.0207 | 39.0 | 1092 | 0.5058 | 0.8958 |
| 0.0234 | 40.0 | 1120 | 0.4981 | 0.8958 |
| 0.021 | 41.0 | 1148 | 0.4928 | 0.9167 |
| 0.0224 | 42.0 | 1176 | 0.4962 | 0.9167 |
| 0.0212 | 43.0 | 1204 | 0.5329 | 0.8958 |
| 0.0208 | 44.0 | 1232 | 0.5727 | 0.8958 |
| 0.0206 | 45.0 | 1260 | 0.5733 | 0.8958 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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