English Whisper Model
This model is a fine-tuned version of openai/whisper-tiny.en on the Medical dataset. It achieves the following results on the evaluation set:
- Loss: 0.0006
- Wer: 2.3779
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: 15
- 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
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0264 | 4.9020 | 500 | 0.0109 | 1.6205 |
| 0.0012 | 9.8039 | 1000 | 0.0009 | 2.2801 |
| 0.0007 | 14.7059 | 1500 | 0.0006 | 2.3779 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Dev372/Cardiology_tiny_1530_1500
Base model
openai/whisper-tiny.en