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: 0.1269
- Wer: 6.2869
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: 18
- 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: 1100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.2361 | 0.2825 | 100 | 1.0425 | 10.4870 |
0.6631 | 0.5650 | 200 | 0.6451 | 9.4908 |
0.419 | 0.8475 | 300 | 0.3854 | 8.5535 |
0.1538 | 1.1299 | 400 | 0.1895 | 7.2635 |
0.1234 | 1.4124 | 500 | 0.1644 | 6.8454 |
0.1134 | 1.6949 | 600 | 0.1470 | 6.6201 |
0.1071 | 1.9774 | 700 | 0.1358 | 6.0289 |
0.0721 | 2.2599 | 800 | 0.1329 | 6.1302 |
0.0693 | 2.5424 | 900 | 0.1299 | 6.3065 |
0.0635 | 2.8249 | 1000 | 0.1275 | 6.5025 |
0.0441 | 3.1073 | 1100 | 0.1269 | 6.2869 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Inference Providers
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Model tree for Dev372/Medical_base_en_1_1v
Base model
openai/whisper-tiny.en