Whisper Small
This model is a fine-tuned version of openai/whisper-small on the Speechocean762_CMUkids_Myst dataset. It achieves the following results on the evaluation set:
- Loss: 0.4052
- Wer: 17.3522
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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use 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: 2048
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.0956 | 1.7544 | 500 | 3.0169 | 17.7308 |
| 3.2000 | 3.5088 | 1000 | 1.8828 | 17.0449 |
| 1.7600 | 5.2632 | 1500 | 1.0183 | 16.4770 |
| 0.8217 | 7.0175 | 2000 | 0.4592 | 18.1182 |
| 0.6692 | 8.7719 | 2500 | 0.4208 | 19.1560 |
| 0.6587 | 10.5263 | 3000 | 0.4109 | 17.5994 |
| 0.6051 | 12.2807 | 3500 | 0.4064 | 17.7931 |
| 0.5749 | 14.0351 | 4000 | 0.4052 | 17.3522 |
Framework versions
- Transformers 5.8.1
- Pytorch 2.5.1+cu121
- Datasets 4.8.5
- Tokenizers 0.22.2