w2v2-ks-jpqd-lr1e-4
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.1228
- Accuracy: 0.9695
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 0
- 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: 15.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.5357 | 1.0 | 399 | 2.7821 | 0.6209 |
| 2.7107 | 2.0 | 798 | 2.7331 | 0.6209 |
| 2.671 | 3.0 | 1197 | 2.7330 | 0.6209 |
| 14.208 | 4.0 | 1596 | 14.2660 | 0.7139 |
| 21.0916 | 5.0 | 1995 | 21.0315 | 0.8104 |
| 24.4471 | 6.0 | 2394 | 24.2357 | 0.9073 |
| 25.366 | 7.0 | 2793 | 25.0893 | 0.9273 |
| 25.1369 | 8.0 | 3192 | 24.8976 | 0.9394 |
| 0.4678 | 9.0 | 3591 | 0.2528 | 0.9435 |
| 0.3576 | 10.0 | 3990 | 0.1873 | 0.9613 |
| 0.3622 | 11.0 | 4389 | 0.1583 | 0.9645 |
| 0.2796 | 12.0 | 4788 | 0.1419 | 0.9666 |
| 0.3157 | 13.0 | 5187 | 0.1327 | 0.9693 |
| 0.2997 | 14.0 | 5586 | 0.1263 | 0.9694 |
| 0.2667 | 15.0 | 5985 | 0.1228 | 0.9695 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2