whisper_IPA_mnx_lr2e5
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: 0.3020
- Wer: 49.8936
- Cer: 10.8822
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 200
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 9.8811 | 1.0 | 94 | 25.8793 | 1.7579 | 90.2119 |
| 4.1492 | 2.0 | 188 | 15.8005 | 1.1126 | 60.9485 |
| 2.7002 | 3.0 | 282 | 12.1085 | 0.9240 | 51.4632 |
| 2.0700 | 4.0 | 376 | 10.6037 | 0.8026 | 45.7114 |
| 1.7341 | 5.0 | 470 | 10.3937 | 0.7765 | 45.3078 |
| 1.3342 | 6.0 | 564 | 9.5888 | 0.8075 | 40.3633 |
| 1.0914 | 7.0 | 658 | 9.0639 | 0.7846 | 40.8678 |
| 0.9527 | 8.0 | 752 | 9.2913 | 0.7992 | 39.4551 |
| 0.7752 | 9.0 | 846 | 8.5914 | 0.7771 | 38.7487 |
| 2.2441 | 10.0 | 940 | 0.5908 | 77.4468 | 30.3030 |
| 1.3215 | 11.0 | 1034 | 0.3993 | 65.8511 | 16.7189 |
| 1.0320 | 12.0 | 1128 | 0.3606 | 61.1702 | 14.9425 |
| 0.8958 | 13.0 | 1222 | 0.3401 | 55.4255 | 12.7034 |
| 0.7670 | 14.0 | 1316 | 0.3020 | 49.8936 | 10.8822 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2