whisper-small-zh-0210
This model is a fine-tuned version of TsaiYing/whisper-small-zh-sample152 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Cer: 0.1581
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: 5e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0105 | 14.2857 | 100 | 0.0015 | 0.1581 |
| 0.0008 | 28.5714 | 200 | 0.0002 | 0.1581 |
| 0.0004 | 42.8571 | 300 | 0.0001 | 0.1581 |
| 0.0003 | 57.1429 | 400 | 0.0001 | 0.1581 |
| 0.0002 | 71.4286 | 500 | 0.0001 | 0.1581 |
| 0.0002 | 85.7143 | 600 | 0.0000 | 0.1581 |
| 0.0002 | 100.0 | 700 | 0.0000 | 0.1581 |
| 0.0002 | 114.2857 | 800 | 0.0000 | 0.1581 |
| 0.0002 | 128.5714 | 900 | 0.0000 | 0.1581 |
| 0.0001 | 142.8571 | 1000 | 0.0000 | 0.1581 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0