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dgx1_w2v2_base_teacher_student_distillation_mozilla_epochs_100_batch_16
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 33.1259
- Wer: 0.9996
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: 16
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- 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: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 81.3268 | 7.35 | 500 | 27.8835 | 0.9996 |
| 62.2215 | 14.7 | 1000 | 28.9444 | 0.9997 |
| 58.4422 | 22.06 | 1500 | 30.4689 | 0.9997 |
| 55.5853 | 29.41 | 2000 | 30.3907 | 0.9996 |
| 53.3674 | 36.76 | 2500 | 31.5643 | 0.9996 |
| 51.3963 | 44.12 | 3000 | 31.6585 | 0.9996 |
| 49.5487 | 51.47 | 3500 | 33.0177 | 0.9996 |
| 48.3909 | 58.82 | 4000 | 33.6293 | 0.9996 |
| 47.6249 | 66.18 | 4500 | 33.1259 | 0.9996 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2
