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ws_w2lm_base_distill_noisy_teacher_libri_epochs_50_batch_8
This model is a fine-tuned version of rohitp1/kkkh_w2lm_base_plus_finetune_teacher_noise_libri360_50_epochs_batch_16 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0945
- Wer: 0.1041
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: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0562 | 2.46 | 250 | 0.0741 | 0.1135 |
| 0.0538 | 4.92 | 500 | 0.0736 | 0.1126 |
| 0.0506 | 7.38 | 750 | 0.0751 | 0.1116 |
| 0.0465 | 9.84 | 1000 | 0.0752 | 0.1099 |
| 0.0424 | 12.31 | 1250 | 0.0762 | 0.1089 |
| 0.0385 | 14.77 | 1500 | 0.0790 | 0.1078 |
| 0.0355 | 17.23 | 1750 | 0.0788 | 0.1062 |
| 0.0335 | 19.69 | 2000 | 0.0795 | 0.1053 |
| 0.0314 | 22.15 | 2250 | 0.0825 | 0.1052 |
| 0.0298 | 24.61 | 2500 | 0.0837 | 0.1055 |
| 0.0285 | 27.07 | 2750 | 0.0873 | 0.1049 |
| 0.0274 | 29.53 | 3000 | 0.0868 | 0.1043 |
| 0.0266 | 32.0 | 3250 | 0.0891 | 0.1044 |
| 0.0256 | 34.46 | 3500 | 0.0902 | 0.1044 |
| 0.0251 | 36.92 | 3750 | 0.0911 | 0.1044 |
| 0.0247 | 39.38 | 4000 | 0.0926 | 0.1042 |
| 0.0242 | 41.84 | 4250 | 0.0936 | 0.1042 |
| 0.0238 | 44.3 | 4500 | 0.0940 | 0.1042 |
| 0.0235 | 46.76 | 4750 | 0.0938 | 0.1042 |
| 0.0233 | 49.22 | 5000 | 0.0945 | 0.1041 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.7.1
- Tokenizers 0.11.0
