whisper_large
This model is a fine-tuned version of openai/whisper-large on the MAICON2023_denoise dataset. It achieves the following results on the evaluation set:
- Loss: 0.2852
- Cer: 22.8829
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: 4
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.5697 | 0.36 | 1000 | 0.5593 | 37.0887 |
| 0.3805 | 0.71 | 2000 | 0.4014 | 30.2776 |
| 0.1647 | 1.07 | 3000 | 0.3255 | 26.6392 |
| 0.1244 | 1.43 | 4000 | 0.2852 | 22.8829 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Base model
openai/whisper-large