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small_finetune_CM01
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9764
- Wer: 1.0
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: 20
- 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: 700
- num_epochs: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
40.8946 | 100.0 | 700 | 3.6118 | 1.0 |
3.1203 | 200.0 | 1400 | 3.4805 | 1.0 |
2.2986 | 300.0 | 2100 | 2.6437 | 1.0 |
1.9839 | 400.0 | 2800 | 2.3215 | 1.0 |
1.7708 | 500.0 | 3500 | 2.2025 | 1.0 |
1.6458 | 600.0 | 4200 | 2.1303 | 1.0 |
1.5592 | 700.0 | 4900 | 2.0806 | 1.0 |
1.4861 | 800.0 | 5600 | 2.0559 | 1.0 |
1.4415 | 900.0 | 6300 | 2.0361 | 1.0 |
1.3975 | 1000.0 | 7000 | 2.0248 | 1.0 |
1.3595 | 1100.0 | 7700 | 2.0246 | 1.0 |
1.3413 | 1200.0 | 8400 | 1.9947 | 1.0 |
1.3142 | 1300.0 | 9100 | 2.0000 | 1.0 |
1.2986 | 1400.0 | 9800 | 1.9909 | 1.0 |
1.2823 | 1500.0 | 10500 | 1.9862 | 1.0 |
1.2724 | 1600.0 | 11200 | 1.9851 | 1.0 |
1.2588 | 1700.0 | 11900 | 1.9862 | 1.0 |
1.2599 | 1800.0 | 12600 | 1.9800 | 1.0 |
1.2536 | 1900.0 | 13300 | 1.9788 | 1.0 |
1.2551 | 2000.0 | 14000 | 1.9764 | 1.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1