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openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3367
- Wer: 11.4692
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0108 | 4.04 | 1000 | 0.2423 | 12.7600 |
| 0.0013 | 9.04 | 2000 | 0.2810 | 11.9799 |
| 0.0001 | 14.04 | 3000 | 0.3152 | 11.5435 |
| 0.0001 | 19.04 | 4000 | 0.3304 | 11.4320 |
| 0.0001 | 24.04 | 5000 | 0.3367 | 11.4692 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
