whisper-test-1
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4129
- Cer: 29.7003
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: 48
- eval_batch_size: 24
- 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 |
|---|---|---|---|---|
| 0.2285 | 8.33 | 500 | 0.6509 | 25.5488 |
| 0.0148 | 16.67 | 1000 | 0.7623 | 28.2401 |
| 0.0022 | 25.0 | 1500 | 0.8702 | 26.6749 |
| 0.0004 | 33.33 | 2000 | 1.0062 | 28.1924 |
| 0.0 | 41.67 | 2500 | 1.1586 | 28.5551 |
| 0.0 | 50.0 | 3000 | 1.2983 | 29.0704 |
| 0.0 | 58.33 | 3500 | 1.3890 | 29.3758 |
| 0.0 | 66.67 | 4000 | 1.4129 | 29.7003 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-base