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subhadeep_whisper_base_finetune_teacher_babble_noise_libri_360_hours_100_epochs_batch_8
This model is a fine-tuned version of openai/whisper-base.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2491
- Wer: 13.5528
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7942 | 1.98 | 100 | 0.2872 | 16.8523 |
| 0.1675 | 3.98 | 200 | 0.2003 | 13.5730 |
| 0.0819 | 5.98 | 300 | 0.1944 | 13.1208 |
| 0.0418 | 7.98 | 400 | 0.2070 | 13.0639 |
| 0.0264 | 9.98 | 500 | 0.2199 | 13.0289 |
| 0.0227 | 11.98 | 600 | 0.2310 | 13.3690 |
| 0.0218 | 13.98 | 700 | 0.2322 | 13.1870 |
| 0.02 | 15.98 | 800 | 0.2405 | 13.1466 |
| 0.0207 | 17.98 | 900 | 0.2496 | 13.4444 |
| 0.0226 | 19.98 | 1000 | 0.2491 | 13.5528 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2
