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banglabert-VITD
This model is a fine-tuned version of csebuetnlp/banglabert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5666
- Accuracy: 0.7887
- F1 score: 0.7873
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 score |
|---|---|---|---|---|---|
| 0.851 | 1.0 | 169 | 0.6329 | 0.7594 | 0.7508 |
| 0.554 | 2.0 | 338 | 0.5666 | 0.7887 | 0.7873 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
