WhisperTiny15hCommonVoice0.0Augment
This model is a fine-tuned version of OpenAI/whisper-tiny on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.9043
- Wer: 0.4284
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8215 | 0.8929 | 500 | 1.0601 | 0.4950 |
| 0.6933 | 1.7857 | 1000 | 0.9860 | 0.4655 |
| 0.5697 | 2.6786 | 1500 | 0.9576 | 0.4548 |
| 0.4809 | 3.5714 | 2000 | 0.9356 | 0.4498 |
| 0.4283 | 4.4643 | 2500 | 0.9220 | 0.4484 |
| 0.3732 | 5.3571 | 3000 | 0.9059 | 0.4624 |
| 0.3367 | 6.25 | 3500 | 0.9070 | 0.4315 |
| 0.3168 | 7.1429 | 4000 | 0.9012 | 0.4284 |
| 0.311 | 8.0357 | 4500 | 0.8957 | 0.4299 |
| 0.2897 | 8.9286 | 5000 | 0.9043 | 0.4284 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0
- Datasets 3.3.0
- Tokenizers 0.21.0