English Whisper Model
This model is a fine-tuned version of openai/whisper-small.en on the Medical dataset. It achieves the following results on the evaluation set:
- Loss: 0.0236
- Wer: 1.2966
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 |
---|---|---|---|---|
0.0026 | 6.0976 | 500 | 0.0240 | 1.6613 |
0.0002 | 12.1951 | 1000 | 0.0234 | 1.2966 |
0.0002 | 18.2927 | 1500 | 0.0236 | 1.2966 |
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_small.en_1530_1500
Base model
openai/whisper-small.en