w2v-bert-2.0-mongolian-colab-CV16.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5207
- Wer: 0.3239
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.8627 | 2.3715 | 300 | 0.6314 | 0.5367 |
| 0.3521 | 4.7431 | 600 | 0.5801 | 0.4462 |
| 0.1757 | 7.1146 | 900 | 0.4910 | 0.3634 |
| 0.0733 | 9.4862 | 1200 | 0.5207 | 0.3239 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.1.2
- Datasets 3.1.0
- Tokenizers 0.20.3
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facebook/w2v-bert-2.0