whisper-medium-sds200
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3857
- Wer: 23.6639
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: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4466 | 0.4327 | 1000 | 0.4548 | 27.8436 |
| 0.3417 | 0.8654 | 2000 | 0.4154 | 26.0740 |
| 0.2122 | 1.2981 | 3000 | 0.3984 | 25.3984 |
| 0.1734 | 1.7309 | 4000 | 0.3851 | 24.1424 |
| 0.1015 | 2.1636 | 5000 | 0.3857 | 23.6639 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-medium