Whisper Tiny
This model is a fine-tuned version of openai/whisper-medium on the Personal - Mimic Recording dataset. It achieves the following results on the evaluation set:
- Loss: 0.1404
- Wer: 0.0645
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 75
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3839 | 0.9932 | 73 | 0.1968 | 0.0975 |
| 0.0763 | 2.0 | 147 | 0.1418 | 0.0879 |
| 0.017 | 2.9932 | 220 | 0.1410 | 0.1200 |
| 0.0058 | 4.0 | 294 | 0.1404 | 0.0645 |
| 0.0014 | 4.9660 | 365 | 0.1396 | 0.0647 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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Base model
openai/whisper-medium