wav2vec2-base-finetune-vi-v5
This model is a fine-tuned version of nguyenvulebinh/wav2vec2-large-vi on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2373
- Wer: 0.1681
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: 5e-05
- train_batch_size: 16
- 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: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
20.4793 | 0.99 | 500 | 8.0023 | 1.0 |
4.5661 | 1.98 | 1000 | 3.4221 | 1.0 |
3.356 | 2.96 | 1500 | 3.2739 | 1.0 |
2.2533 | 3.95 | 2000 | 0.8992 | 0.4884 |
0.8412 | 4.94 | 2500 | 0.5181 | 0.3061 |
0.5738 | 5.93 | 3000 | 0.3986 | 0.2586 |
0.4608 | 6.92 | 3500 | 0.3545 | 0.2230 |
0.399 | 7.91 | 4000 | 0.3220 | 0.2003 |
0.341 | 8.89 | 4500 | 0.2936 | 0.1928 |
0.3094 | 9.88 | 5000 | 0.2727 | 0.1873 |
0.2834 | 10.87 | 5500 | 0.2721 | 0.1813 |
0.2761 | 11.86 | 6000 | 0.2704 | 0.1817 |
0.2505 | 12.85 | 6500 | 0.2597 | 0.1766 |
0.2472 | 13.83 | 7000 | 0.2460 | 0.1744 |
0.2335 | 14.82 | 7500 | 0.2486 | 0.1728 |
0.2183 | 15.81 | 8000 | 0.2430 | 0.1714 |
0.2153 | 16.8 | 8500 | 0.2433 | 0.1697 |
0.2029 | 17.79 | 9000 | 0.2408 | 0.1688 |
0.2094 | 18.77 | 9500 | 0.2349 | 0.1694 |
0.2045 | 19.76 | 10000 | 0.2373 | 0.1681 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.8.0
- Tokenizers 0.13.3
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