bengali_pos_v1
This model is a fine-tuned version of csebuetnlp/banglabert on the pos_tag_100k dataset. It achieves the following results on the evaluation set:
- Loss: 0.6322
- Precision: 0.7541
- Recall: 0.7567
- F1: 0.7554
- Accuracy: 0.8182
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.7003 | 1.0 | 20000 | 0.6762 | 0.7281 | 0.7339 | 0.7310 | 0.8000 |
0.6097 | 2.0 | 40000 | 0.6277 | 0.7481 | 0.7481 | 0.7481 | 0.8135 |
0.5062 | 3.0 | 60000 | 0.6322 | 0.7541 | 0.7567 | 0.7554 | 0.8182 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Evaluation results
- Precision on pos_tag_100kvalidation set self-reported0.754
- Recall on pos_tag_100kvalidation set self-reported0.757
- F1 on pos_tag_100kvalidation set self-reported0.755
- Accuracy on pos_tag_100kvalidation set self-reported0.818