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WAVLM_TITML_IDN_model
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7585
- Accuracy: 0.8181
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 8.0217 | 0.98 | 31 | 7.7416 | 0.0472 |
| 5.1076 | 2.0 | 63 | 3.5170 | 0.0472 |
| 3.0131 | 2.98 | 94 | 2.9921 | 0.0876 |
| 3.0119 | 4.0 | 126 | 2.9580 | 0.0928 |
| 2.685 | 4.98 | 157 | 2.6591 | 0.0793 |
| 2.4513 | 6.0 | 189 | 2.3831 | 0.1257 |
| 2.4415 | 6.98 | 220 | 2.3518 | 0.1415 |
| 2.2998 | 8.0 | 252 | 2.2327 | 0.1864 |
| 2.1987 | 8.98 | 283 | 2.1297 | 0.1549 |
| 2.1206 | 10.0 | 315 | 2.0529 | 0.2118 |
| 2.0542 | 10.98 | 346 | 1.9592 | 0.2507 |
| 1.9693 | 12.0 | 378 | 1.8652 | 0.2792 |
| 1.8677 | 12.98 | 409 | 1.7811 | 0.3668 |
| 1.7369 | 14.0 | 441 | 1.7902 | 0.2493 |
| 1.6551 | 14.98 | 472 | 1.6558 | 0.3406 |
| 1.6176 | 16.0 | 504 | 1.5724 | 0.3585 |
| 1.5666 | 16.98 | 535 | 1.5822 | 0.4207 |
| 1.5103 | 18.0 | 567 | 1.5028 | 0.4379 |
| 1.4695 | 18.98 | 598 | 1.4276 | 0.4970 |
| 1.3016 | 20.0 | 630 | 1.3621 | 0.4798 |
| 1.2025 | 20.98 | 661 | 1.2016 | 0.5778 |
| 1.1211 | 22.0 | 693 | 1.2346 | 0.5644 |
| 1.0204 | 22.98 | 724 | 1.0743 | 0.6445 |
| 0.9365 | 24.0 | 756 | 1.0121 | 0.6759 |
| 0.8553 | 24.98 | 787 | 0.9246 | 0.7290 |
| 0.7698 | 26.0 | 819 | 0.8603 | 0.7612 |
| 0.7336 | 26.98 | 850 | 0.8072 | 0.7867 |
| 0.6965 | 28.0 | 882 | 0.7770 | 0.8009 |
| 0.6662 | 28.98 | 913 | 0.7640 | 0.8136 |
| 0.63 | 29.52 | 930 | 0.7585 | 0.8181 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
