<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
dgx1_whisper_base_libri360_noisy_teacher_distil_epochs_50_batch_8
This model is a fine-tuned version of rohitp1/subhadeep_whisper_base_finetune_teacher_babble_noise_libri_360_hours_100_epochs_batch_8 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5761
- Wer: 10.6733
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: 5e-05
- 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_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0423 | 1.48 | 150 | 0.1620 | 10.8902 |
| 0.0999 | 2.96 | 300 | 0.2030 | 10.7882 |
| 0.1577 | 4.45 | 450 | 0.2511 | 10.7937 |
| 0.2078 | 5.94 | 600 | 0.2966 | 10.7827 |
| 0.252 | 7.42 | 750 | 0.3321 | 10.7524 |
| 0.2841 | 8.91 | 900 | 0.3625 | 10.7588 |
| 0.3189 | 10.39 | 1050 | 0.3858 | 10.7772 |
| 0.341 | 11.88 | 1200 | 0.4090 | 10.7505 |
| 0.5277 | 13.36 | 1350 | 0.5461 | 11.1926 |
| 0.8342 | 14.85 | 1500 | 0.5250 | 10.8415 |
| 0.8278 | 16.33 | 1650 | 0.5543 | 10.7478 |
| 0.8255 | 17.82 | 1800 | 0.5481 | 10.6761 |
| 0.822 | 19.31 | 1950 | 0.5504 | 10.6650 |
| 0.8204 | 20.79 | 2100 | 0.5556 | 10.6650 |
| 0.8246 | 22.28 | 2250 | 0.5598 | 10.6586 |
| 0.8228 | 23.76 | 2400 | 0.5634 | 10.6770 |
| 0.8282 | 25.25 | 2550 | 0.5670 | 10.6706 |
| 0.8264 | 26.73 | 2700 | 0.5702 | 10.6752 |
| 0.8298 | 28.22 | 2850 | 0.5731 | 10.6908 |
| 0.8273 | 29.7 | 3000 | 0.5761 | 10.6733 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2
