bengali_pos_v1_500000
This model is a fine-tuned version of mHossain/bengali_pos_v1_400000 on the pos_tag_100k dataset. It achieves the following results on the evaluation set:
- Loss: 0.6185
- Precision: 0.7517
- Recall: 0.7533
- F1: 0.7525
- Accuracy: 0.8149
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 |
|---|---|---|---|---|---|---|---|
| 0.6508 | 1.0 | 67500 | 0.6325 | 0.7386 | 0.7396 | 0.7391 | 0.8041 |
| 0.5713 | 2.0 | 135000 | 0.6093 | 0.7487 | 0.7500 | 0.7493 | 0.8123 |
| 0.4789 | 3.0 | 202500 | 0.6185 | 0.7517 | 0.7533 | 0.7525 | 0.8149 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for mHossain/bengali_pos_v1_500000
Base model
mHossain/bengali_pos_v1_400000
Finetuned
mHossain/bengali_pos_v1_300000
Finetuned
mHossain/bengali_pos_v1_400000
Evaluation results
- Precision on pos_tag_100kvalidation set self-reported0.752
- Recall on pos_tag_100kvalidation set self-reported0.753
- F1 on pos_tag_100kvalidation set self-reported0.753
- Accuracy on pos_tag_100kvalidation set self-reported0.815