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Whisper Small ML - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2308
- Wer: 36.7397
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: 64
- eval_batch_size: 32
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1275 | 4.03 | 500 | 0.1630 | 35.4015 |
| 0.09 | 9.02 | 1000 | 0.1821 | 40.0243 |
| 0.062 | 14.01 | 1500 | 0.2004 | 37.7129 |
| 0.0441 | 19.0 | 2000 | 0.2105 | 36.2530 |
| 0.0335 | 23.03 | 2500 | 0.2250 | 37.7129 |
| 0.0276 | 28.02 | 3000 | 0.2308 | 36.7397 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
