whisper-small-clean_4
This model is a fine-tuned version of openai/whisper-small on the lyhourt/clean_4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0801
- Wer: 11.3744
Model description
More information needed
Intended uses & limitations
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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: 50
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0466 | 0.3333 | 100 | 0.1170 | 15.9953 |
| 0.2315 | 1.0333 | 200 | 0.0852 | 12.6777 |
| 0.0031 | 1.3667 | 300 | 0.0801 | 11.3744 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-small