metadata
base_model: csebuetnlp/banglabert
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: banglabert-MLTC-BB
results: []
banglabert-MLTC-BB
This model is a fine-tuned version of csebuetnlp/banglabert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3626
- F1: 0.8666
- Roc Auc: 0.8624
- Accuracy: 0.5861
- Hamming Loss: 0.1375
- Jaccard Score: 0.7646
- Zero One Loss: 0.4139
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
|---|---|---|---|---|---|---|---|---|---|
| 0.4962 | 1.0 | 73 | 0.4868 | 0.8020 | 0.7962 | 0.4730 | 0.2037 | 0.6694 | 0.5270 |
| 0.3992 | 2.0 | 146 | 0.3993 | 0.8420 | 0.8386 | 0.5656 | 0.1613 | 0.7272 | 0.4344 |
| 0.3163 | 3.0 | 219 | 0.3647 | 0.8616 | 0.8586 | 0.5810 | 0.1414 | 0.7569 | 0.4190 |
| 0.2545 | 4.0 | 292 | 0.3626 | 0.8666 | 0.8624 | 0.5861 | 0.1375 | 0.7646 | 0.4139 |
| 0.2464 | 5.0 | 365 | 0.3537 | 0.8626 | 0.8612 | 0.5835 | 0.1388 | 0.7584 | 0.4165 |
| 0.2534 | 6.0 | 438 | 0.3591 | 0.8600 | 0.8566 | 0.5707 | 0.1433 | 0.7544 | 0.4293 |
| 0.194 | 7.0 | 511 | 0.3525 | 0.8644 | 0.8624 | 0.5938 | 0.1375 | 0.7612 | 0.4062 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1