Whisper-Small Augmented for SEP-28k
This model is a fine-tuned version of openai/whisper-small on the SEP-28K dataset. It achieves the following results on the evaluation set:
- Loss: 0.7265
- Wer: 13.7591
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5910
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0229 | 5.1020 | 1000 | 0.5061 | 13.5547 |
| 0.0018 | 10.2041 | 2000 | 0.6259 | 13.6204 |
| 0.0006 | 15.3061 | 3000 | 0.6754 | 13.6496 |
| 0.0005 | 20.4082 | 4000 | 0.7105 | 13.7007 |
| 0.0004 | 25.5102 | 5000 | 0.7265 | 13.7591 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for justanotherinternetguy/whisper-small-sep28
Base model
openai/whisper-small