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Whisper Tiny Pl
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6919
- Wer: 39.4696
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: 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 |
|---|---|---|---|---|
| 0.3647 | 1.05 | 500 | 0.6999 | 43.0430 |
| 0.2752 | 3.04 | 1000 | 0.6002 | 39.3275 |
| 0.2513 | 5.04 | 1500 | 0.5911 | 37.8643 |
| 0.1661 | 7.04 | 2000 | 0.6381 | 37.6887 |
| 0.154 | 9.03 | 2500 | 0.6157 | 37.9362 |
| 0.1126 | 11.03 | 3000 | 0.6319 | 38.6402 |
| 0.0763 | 13.02 | 3500 | 0.6539 | 38.9730 |
| 0.0729 | 15.02 | 4000 | 0.6583 | 38.9362 |
| 0.0778 | 17.02 | 4500 | 0.6653 | 39.6769 |
| 0.0698 | 19.01 | 5000 | 0.6919 | 39.4696 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
