Fine_tune_whisper_small
This model is a fine-tuned version of openai/whisper-small on our own recorded dataset (700 audio samples). It achieves the following results on the evaluation set:
- Loss: 0.8225
- Wer: 43.7477
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: 200
- training_steps: 900
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2991 | 3.92 | 200 | 0.6605 | 44.1903 |
0.0185 | 7.84 | 400 | 0.7377 | 42.8624 |
0.0026 | 11.76 | 600 | 0.8087 | 43.0837 |
0.0011 | 15.69 | 800 | 0.8225 | 43.7477 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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