whisper-small-ft-common-language-id
This model is a fine-tuned version of openai/whisper-small on the common_language dataset. It achieves the following results on the evaluation set:
- Loss: 0.6409
- Accuracy: 0.8860
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: 16
- seed: 0
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1767 | 1.0 | 694 | 1.1063 | 0.7514 |
| 0.582 | 2.0 | 1388 | 0.6595 | 0.8327 |
| 0.3172 | 3.0 | 2082 | 0.5887 | 0.8529 |
| 0.196 | 4.0 | 2776 | 0.5332 | 0.8701 |
| 0.0858 | 5.0 | 3470 | 0.5705 | 0.8733 |
| 0.0477 | 6.0 | 4164 | 0.6311 | 0.8779 |
| 0.0353 | 7.0 | 4858 | 0.6011 | 0.8825 |
| 0.0033 | 8.0 | 5552 | 0.6186 | 0.8843 |
| 0.0071 | 9.0 | 6246 | 0.6409 | 0.8860 |
| 0.0074 | 10.0 | 6940 | 0.6334 | 0.8860 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2