Whisper Fine-tuned - NNCES
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1135
- Wer: 8.0963
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: 4
- 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: 5
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.2697 | 0.1 | 10 | 0.8252 | 40.9920 |
| 0.6597 | 0.2 | 20 | 0.5482 | 25.2371 |
| 0.4656 | 0.3 | 30 | 0.3488 | 20.0584 |
| 0.2774 | 0.4 | 40 | 0.2164 | 21.5901 |
| 0.1746 | 0.5 | 50 | 0.1770 | 19.0372 |
| 0.1826 | 0.6 | 60 | 0.1540 | 15.3902 |
| 0.1228 | 0.7 | 70 | 0.1364 | 11.4515 |
| 0.1271 | 0.8 | 80 | 0.1246 | 8.6798 |
| 0.2388 | 0.9 | 90 | 0.1165 | 8.0233 |
| 0.2584 | 1.0 | 100 | 0.1135 | 8.0963 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
openai/whisper-tiny