whisper-large-v3-turbo_finetuned-2
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1808
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: 64
- eval_batch_size: 64
- seed: 42
- 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_ratio: 0.1
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1627 | 1.1696 | 1000 | 0.1909 |
| 0.1081 | 2.3392 | 2000 | 0.1793 |
| 0.0722 | 3.5088 | 3000 | 0.1790 |
| 0.0526 | 4.6784 | 4000 | 0.1808 |
Framework versions
- Transformers 4.52.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1