Whisper Tiny English v2
This model is a fine-tuned version of openai/whisper-tiny on the commands_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0003
- Wer: 3.3333
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: 30
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0098 | 1.0 | 75 | 0.0038 | 3.3333 |
| 0.0035 | 2.0 | 150 | 0.0006 | 3.75 |
| 0.0031 | 3.0 | 225 | 0.0004 | 3.1667 |
| 0.0012 | 4.0 | 300 | 0.0003 | 3.3333 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
openai/whisper-tiny