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whisper-med-asd_v2
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5457
- Wer: 37.9455
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1323 | 10.53 | 100 | 0.5968 | 71.875 |
| 0.0052 | 21.05 | 200 | 0.7108 | 77.7778 |
| 0.0005 | 31.58 | 300 | 0.7444 | 81.25 |
| 0.0004 | 42.11 | 400 | 0.7615 | 80.9028 |
| 0.0003 | 52.63 | 500 | 0.7780 | 79.8611 |
| 0.0003 | 63.16 | 600 | 0.7941 | 80.9028 |
| 0.0003 | 73.68 | 700 | 0.8077 | 80.9028 |
| 0.0003 | 84.21 | 800 | 0.8194 | 79.1667 |
| 0.0003 | 94.74 | 900 | 0.8276 | 79.5139 |
| 0.0003 | 105.26 | 1000 | 0.8305 | 79.1667 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
