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large_config
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2441
- Wer: 17.8570
- Cer: 8.0073
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: 42
- 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_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.5155 | 0.1 | 1000 | 0.4045 | 27.7845 | 12.1308 |
| 0.5436 | 1.02 | 2000 | 0.3784 | 27.0983 | 11.9181 |
| 0.265 | 1.12 | 3000 | 0.3227 | 22.8815 | 10.0236 |
| 0.4765 | 2.04 | 4000 | 0.3021 | 21.9744 | 9.6005 |
| 0.1818 | 2.14 | 5000 | 0.3002 | 21.0336 | 9.1830 |
| 0.4031 | 3.05 | 6000 | 0.2496 | 18.0914 | 7.9181 |
| 0.1991 | 3.15 | 7000 | 0.2971 | 21.7029 | 9.9984 |
| 0.3023 | 4.07 | 8000 | 0.2445 | 17.7946 | 7.9248 |
| 0.2185 | 4.17 | 9000 | 0.2842 | 20.3760 | 9.2891 |
| 0.2114 | 5.09 | 10000 | 0.2441 | 17.8570 | 8.0073 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
