Whisper Tiny English - Francesco Bonzi
This model is a fine-tuned version of openai/whisper-tiny on the LibriSpeech ASR dataset. It achieves the following results on the evaluation set:
- Loss: 0.1858
- Wer: 6.6000
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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1884 | 0.56 | 1000 | 0.2044 | 7.2257 |
| 0.1119 | 1.12 | 2000 | 0.1911 | 6.8510 |
| 0.1203 | 1.68 | 3000 | 0.1873 | 6.6038 |
| 0.0832 | 2.24 | 4000 | 0.1858 | 6.6000 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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