whisper-tiny-orm-victor
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5053
- Wer: 0.3413
- Cer: 0.1054
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- 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
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.6345 | 0.4195 | 500 | 0.6676 | 0.4803 | 0.1677 |
| 0.5221 | 0.8389 | 1000 | 0.5620 | 0.4046 | 0.1331 |
| 0.4200 | 1.2584 | 1500 | 0.5361 | 0.3759 | 0.1169 |
| 0.4088 | 1.6779 | 2000 | 0.5015 | 0.3635 | 0.1149 |
| 0.3198 | 2.0973 | 2500 | 0.4984 | 0.3467 | 0.1054 |
| 0.3386 | 2.5168 | 3000 | 0.4911 | 0.3410 | 0.1026 |
| 0.3245 | 2.9362 | 3500 | 0.4801 | 0.3401 | 0.1039 |
| 0.2734 | 3.3557 | 4000 | 0.4916 | 0.3408 | 0.1045 |
| 0.2750 | 3.7752 | 4500 | 0.4841 | 0.3374 | 0.1041 |
| 0.2215 | 4.1946 | 5000 | 0.5053 | 0.3413 | 0.1054 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Downloads last month
- 203
Model tree for waxal-benchmarking/whisper-tiny-orm-victor
Base model
openai/whisper-tiny