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w2v2-libri
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: 1.7315
- Wer: 0.5574
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.1828 | 50.0 | 200 | 3.0563 | 1.0 |
| 2.8849 | 100.0 | 400 | 2.9023 | 1.0 |
| 1.5108 | 150.0 | 600 | 1.1468 | 0.6667 |
| 0.1372 | 200.0 | 800 | 1.3749 | 0.6279 |
| 0.0816 | 250.0 | 1000 | 1.3985 | 0.6224 |
| 0.0746 | 300.0 | 1200 | 1.5285 | 0.6141 |
| 0.0556 | 350.0 | 1400 | 1.5496 | 0.5920 |
| 0.0644 | 400.0 | 1600 | 1.6263 | 0.5947 |
| 0.0546 | 450.0 | 1800 | 1.6803 | 0.5906 |
| 0.0491 | 500.0 | 2000 | 1.6155 | 0.5837 |
| 0.0518 | 550.0 | 2200 | 1.6784 | 0.5698 |
| 0.0314 | 600.0 | 2400 | 1.6050 | 0.5602 |
| 0.0048 | 650.0 | 2600 | 1.7703 | 0.5546 |
| 0.0042 | 700.0 | 2800 | 1.7135 | 0.5615 |
| 0.0025 | 750.0 | 3000 | 1.7315 | 0.5574 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 1.18.3
- Tokenizers 0.13.2
