whisper-small-ham - Charles Brain
This model is a fine-tuned version of openai/whisper-small on the hamradio_voice_1_0 dataset. This is highly experimental and does not have much training data yet. That will be the next 'challenge'.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0
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: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0 | 1000.0 | 1000 | 0.0000 | 0.0 |
| 0.0 | 2000.0 | 2000 | 0.0000 | 0.0 |
| 0.0 | 3000.0 | 3000 | 0.0000 | 0.0 |
| 0.0 | 4000.0 | 4000 | 0.0000 | 0.0 |
| 0.0 | 5000.0 | 5000 | 0.0000 | 0.0 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.1+cu130
- Datasets 4.5.0
- Tokenizers 0.22.2
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openai/whisper-small