w_medium
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7098
- Wer: 74.8294
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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7765 | 0.4548 | 1000 | 0.7543 | 130.5512 |
| 0.6989 | 0.9095 | 2000 | 0.6826 | 74.6797 |
| 0.4569 | 1.3643 | 3000 | 0.6605 | 80.5546 |
| 0.4813 | 1.8190 | 4000 | 0.6465 | 79.3330 |
| 0.3847 | 2.2738 | 5000 | 0.6780 | 73.8704 |
| 0.3865 | 2.7285 | 6000 | 0.6712 | 82.8552 |
| 0.2736 | 3.1833 | 7000 | 0.7016 | 75.8153 |
| 0.2428 | 3.6380 | 8000 | 0.7098 | 74.8294 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
openai/whisper-medium