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dat259-wav2vec2-en2-copy
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.5429
- Wer: 0.5569
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.5149 | 1.82 | 200 | 3.0474 | 1.0 |
| 2.0483 | 3.64 | 400 | 1.8004 | 0.7808 |
| 0.5464 | 5.45 | 600 | 1.5242 | 0.6529 |
| 0.3269 | 7.27 | 800 | 1.3820 | 0.6046 |
| 0.2337 | 9.09 | 1000 | 1.4605 | 0.5866 |
| 0.1863 | 10.91 | 1200 | 1.5567 | 0.5864 |
| 0.1531 | 12.73 | 1400 | 1.5787 | 0.5871 |
| 0.1326 | 14.55 | 1600 | 1.5766 | 0.5679 |
| 0.1118 | 16.36 | 1800 | 1.4709 | 0.5566 |
| 0.1017 | 18.18 | 2000 | 1.5455 | 0.5598 |
| 0.0955 | 20.0 | 2200 | 1.5429 | 0.5569 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
