Whisper Small ganda
This model is a fine-tuned version of openai/whisper-small on the Yogera data dataset. It achieves the following results on the evaluation set:
- Loss: 1.4937
- Wer: 54.2763
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9882 | 26.0 | 500 | 1.4647 | 54.9342 |
| 0.0026 | 52.0 | 1000 | 1.3967 | 60.8553 |
| 0.0002 | 78.0 | 1500 | 1.4295 | 57.8947 |
| 0.0001 | 105.0 | 2000 | 1.4494 | 58.2237 |
| 0.0001 | 131.0 | 2500 | 1.4713 | 53.9474 |
| 0.0001 | 157.0 | 3000 | 1.4835 | 54.2763 |
| 0.0001 | 184.0 | 3500 | 1.4908 | 54.2763 |
| 0.0001 | 210.0 | 4000 | 1.4937 | 54.2763 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Base model
openai/whisper-small