whisper-medium-SIT_20_07_26_0257
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0618
- Wer: 2.4520
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.2725 | 1.0 | 46 | 0.0754 | 4.3075 |
| 0.0995 | 2.0 | 92 | 0.0574 | 2.8496 |
| 0.0431 | 3.0 | 138 | 0.0583 | 3.1146 |
| 0.0184 | 4.0 | 184 | 0.0634 | 2.5845 |
| 0.0032 | 5.0 | 230 | 0.0618 | 2.4520 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 2.19.0
- Tokenizers 0.22.2