w2v-bert-2.0-mn-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: 0.5152
- Wer: 0.3237
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 |
|---|---|---|---|---|
| 1.8121 | 2.3715 | 300 | 0.6300 | 0.5082 |
| 0.3404 | 4.7431 | 600 | 0.5988 | 0.4459 |
| 0.1726 | 7.1146 | 900 | 0.4940 | 0.3769 |
| 0.0708 | 9.4862 | 1200 | 0.5152 | 0.3237 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
facebook/w2v-bert-2.0