study0703
This model is a fine-tuned version of openai/whisper-base on the train dataset. It achieves the following results on the evaluation set:
- Loss: 0.1988
- Cer: 6.6313
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.004 | 9.6154 | 1000 | 0.1731 | 6.3102 |
| 0.0007 | 19.2308 | 2000 | 0.1849 | 6.3584 |
| 0.0004 | 28.8462 | 3000 | 0.1921 | 6.4226 |
| 0.0003 | 38.4615 | 4000 | 0.1968 | 6.5992 |
| 0.0002 | 48.0769 | 5000 | 0.1988 | 6.6313 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-base