whisper-order-finetuned-bg
This model is a fine-tuned version of emonidi/whisper-order-finetuned-bg on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 0.0
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0011 | 4.0 | 5 | 0.0016 | 0.0 |
| 0.0001 | 7.38 | 10 | 0.0003 | 0.0 |
| 0.0001 | 11.0 | 15 | 0.0002 | 0.0 |
| 0.0 | 14.77 | 20 | 0.0001 | 0.0 |
| 0.0 | 18.0 | 25 | 0.0001 | 0.0 |
| 0.0 | 22.0 | 30 | 0.0001 | 0.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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