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wav2vec2-base
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.0808
- Wer: 1.0
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.7118 | 0.5 | 500 | 3.0635 | 1.0 |
| 2.9533 | 1.01 | 1000 | 3.0383 | 1.0 |
| 2.9493 | 1.51 | 1500 | 3.0638 | 1.0 |
| 2.9495 | 2.01 | 2000 | 3.0554 | 1.0 |
| 2.9468 | 2.51 | 2500 | 3.0630 | 1.0 |
| 2.9493 | 3.02 | 3000 | 3.0530 | 1.0 |
| 2.9457 | 3.52 | 3500 | 3.0534 | 1.0 |
| 2.9492 | 4.02 | 4000 | 3.0357 | 1.0 |
| 2.9444 | 4.52 | 4500 | 3.0366 | 1.0 |
| 2.9495 | 5.03 | 5000 | 3.0412 | 1.0 |
| 2.9468 | 5.53 | 5500 | 3.0331 | 1.0 |
| 2.9453 | 6.03 | 6000 | 3.0847 | 1.0 |
| 2.9484 | 6.53 | 6500 | 3.0661 | 1.0 |
| 2.9457 | 7.04 | 7000 | 3.0769 | 1.0 |
| 2.9449 | 7.54 | 7500 | 3.0701 | 1.0 |
| 2.9453 | 8.04 | 8000 | 3.1072 | 1.0 |
| 2.9436 | 8.54 | 8500 | 3.1043 | 1.0 |
| 2.9474 | 9.05 | 9000 | 3.0902 | 1.0 |
| 2.9452 | 9.55 | 9500 | 3.0879 | 1.0 |
| 2.9443 | 10.05 | 10000 | 3.1112 | 1.0 |
| 2.9436 | 10.55 | 10500 | 3.0946 | 1.0 |
| 2.9469 | 11.06 | 11000 | 3.0812 | 1.0 |
| 2.9434 | 11.56 | 11500 | 3.1112 | 1.0 |
| 2.9442 | 12.06 | 12000 | 3.0855 | 1.0 |
| 2.9436 | 12.56 | 12500 | 3.0786 | 1.0 |
| 2.9425 | 13.07 | 13000 | 3.0789 | 1.0 |
| 2.9418 | 13.57 | 13500 | 3.0786 | 1.0 |
| 2.9443 | 14.07 | 14000 | 3.0798 | 1.0 |
| 2.9449 | 14.57 | 14500 | 3.0808 | 1.0 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.10.3
