testing_tensorboard_w_new_access_token
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 3.1867
- Wer: 1.0
- Cer: 0.9653
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: constant
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
3.3114 | 0.6154 | 200 | 3.2030 | 1.0 | 1.0 |
3.1797 | 1.2308 | 400 | 3.1973 | 1.0 | 1.0 |
3.1791 | 1.8462 | 600 | 3.1899 | 1.0 | 1.0 |
3.1767 | 2.4615 | 800 | 3.1787 | 1.0 | 1.0 |
3.1681 | 3.0769 | 1000 | 3.1870 | 1.0 | 0.9987 |
3.1783 | 3.6923 | 1200 | 3.1996 | 0.9998 | 0.9822 |
3.167 | 4.3077 | 1400 | 3.1726 | 1.0 | 1.0 |
3.171 | 4.9231 | 1600 | 3.1743 | 1.0 | 0.9653 |
3.1654 | 5.5385 | 1800 | 3.1926 | 1.0000 | 0.9487 |
3.1714 | 6.1538 | 2000 | 3.1700 | 1.0 | 0.9653 |
3.1638 | 6.7692 | 2200 | 3.1688 | 1.0 | 0.9653 |
3.164 | 7.3846 | 2400 | 3.1934 | 1.0000 | 0.9487 |
3.1729 | 8.0 | 2600 | 3.1689 | 1.0 | 0.9653 |
3.1652 | 8.6154 | 2800 | 3.1660 | 1.0 | 0.9653 |
3.1569 | 9.2308 | 3000 | 3.1890 | 1.0000 | 0.9487 |
3.1639 | 9.8462 | 3200 | 3.1867 | 1.0 | 0.9653 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
facebook/w2v-bert-2.0