openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1929
- Wer: 4.3549
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0326 | 10.0 | 500 | 0.1670 | 5.0398 |
| 0.0019 | 20.0 | 1000 | 0.1728 | 4.5113 |
| 0.0008 | 30.01 | 1500 | 0.1820 | 4.4071 |
| 0.0005 | 40.01 | 2000 | 0.1847 | 4.3773 |
| 0.0004 | 51.0 | 2500 | 0.1886 | 4.3549 |
| 0.0003 | 61.0 | 3000 | 0.1910 | 4.3475 |
| 0.0003 | 71.01 | 3500 | 0.1925 | 4.3549 |
| 0.0002 | 81.01 | 4000 | 0.1929 | 4.3549 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
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