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NLP_Project
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5308
- Wer: 0.3428
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.5939 | 1.0 | 500 | 2.1356 | 1.0014 |
| 0.9126 | 2.01 | 1000 | 0.5469 | 0.5354 |
| 0.4491 | 3.01 | 1500 | 0.4636 | 0.4503 |
| 0.3008 | 4.02 | 2000 | 0.4269 | 0.4330 |
| 0.2229 | 5.02 | 2500 | 0.4164 | 0.4073 |
| 0.188 | 6.02 | 3000 | 0.4717 | 0.4107 |
| 0.1739 | 7.03 | 3500 | 0.4306 | 0.4031 |
| 0.159 | 8.03 | 4000 | 0.4394 | 0.3993 |
| 0.1342 | 9.04 | 4500 | 0.4462 | 0.3904 |
| 0.1093 | 10.04 | 5000 | 0.4387 | 0.3759 |
| 0.1005 | 11.04 | 5500 | 0.5033 | 0.3847 |
| 0.0857 | 12.05 | 6000 | 0.4805 | 0.3876 |
| 0.0779 | 13.05 | 6500 | 0.5269 | 0.3810 |
| 0.072 | 14.06 | 7000 | 0.5109 | 0.3710 |
| 0.0641 | 15.06 | 7500 | 0.4865 | 0.3638 |
| 0.0584 | 16.06 | 8000 | 0.5041 | 0.3646 |
| 0.0552 | 17.07 | 8500 | 0.4987 | 0.3537 |
| 0.0535 | 18.07 | 9000 | 0.4947 | 0.3586 |
| 0.0475 | 19.08 | 9500 | 0.5237 | 0.3647 |
| 0.042 | 20.08 | 10000 | 0.5338 | 0.3561 |
| 0.0416 | 21.08 | 10500 | 0.5068 | 0.3483 |
| 0.0358 | 22.09 | 11000 | 0.5126 | 0.3532 |
| 0.0334 | 23.09 | 11500 | 0.5213 | 0.3536 |
| 0.0331 | 24.1 | 12000 | 0.5378 | 0.3496 |
| 0.03 | 25.1 | 12500 | 0.5167 | 0.3470 |
| 0.0254 | 26.1 | 13000 | 0.5245 | 0.3418 |
| 0.0233 | 27.11 | 13500 | 0.5393 | 0.3456 |
| 0.0232 | 28.11 | 14000 | 0.5279 | 0.3425 |
| 0.022 | 29.12 | 14500 | 0.5308 | 0.3428 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
