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openai/whisper-medium
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: 0.1594
- Wer: 21.8343
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
- 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 | Wer |
|---|---|---|---|---|
| 0.0269 | 5.0 | 500 | 0.1069 | 118.0302 |
| 0.0049 | 10.01 | 1000 | 0.1263 | 135.2788 |
| 0.0009 | 15.01 | 1500 | 0.1355 | 94.5731 |
| 0.0001 | 20.01 | 2000 | 0.1413 | 7.5188 |
| 0.0001 | 25.01 | 2500 | 0.1515 | 7.2508 |
| 0.0001 | 30.02 | 3000 | 0.1568 | 24.8493 |
| 0.0 | 35.02 | 3500 | 0.1588 | 22.1470 |
| 0.0 | 40.02 | 4000 | 0.1594 | 21.8343 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
