Whisper Medium PL
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3739
- Wer: 8.8206
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: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.121 | 0.1 | 500 | 0.2630 | 10.2804 |
| 0.0474 | 1.1 | 1000 | 0.2561 | 9.5597 |
| 0.0257 | 2.09 | 1500 | 0.2617 | 9.5681 |
| 0.0119 | 3.09 | 2000 | 0.2901 | 9.1534 |
| 0.0064 | 4.08 | 2500 | 0.3463 | 9.0280 |
| 0.0045 | 5.08 | 3000 | 0.3151 | 9.0965 |
| 0.0015 | 6.08 | 3500 | 0.3985 | 8.9611 |
| 0.0007 | 7.07 | 4000 | 0.4218 | 8.8073 |
| 0.0006 | 8.07 | 4500 | 0.4054 | 8.8156 |
| 0.0005 | 9.07 | 5000 | 0.3739 | 8.8206 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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