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---
base_model: csebuetnlp/banglabert
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: banglabert-MLTC-BB1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# banglabert-MLTC-BB1
This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3577
- F1: 0.8555
- F1 Weighted: 0.8534
- Roc Auc: 0.8534
- Accuracy: 0.5733
- Hamming Loss: 0.1465
- Jaccard Score: 0.7475
- Zero One Loss: 0.4267
## 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: 24
- eval_batch_size: 24
- 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 | F1 Weighted | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
| 0.5579 | 1.0 | 49 | 0.5012 | 0.7993 | 0.7864 | 0.7832 | 0.4267 | 0.2166 | 0.6657 | 0.5733 |
| 0.4039 | 2.0 | 98 | 0.4338 | 0.8318 | 0.8287 | 0.8218 | 0.5347 | 0.1780 | 0.7121 | 0.4653 |
| 0.3704 | 3.0 | 147 | 0.3728 | 0.8600 | 0.8604 | 0.8560 | 0.5861 | 0.1440 | 0.7544 | 0.4139 |
| 0.3117 | 4.0 | 196 | 0.3615 | 0.8568 | 0.8553 | 0.8528 | 0.5733 | 0.1472 | 0.7495 | 0.4267 |
| 0.2723 | 5.0 | 245 | 0.3514 | 0.8548 | 0.8537 | 0.8528 | 0.5784 | 0.1472 | 0.7464 | 0.4216 |
| 0.2709 | 6.0 | 294 | 0.3640 | 0.8469 | 0.8434 | 0.8438 | 0.5476 | 0.1562 | 0.7344 | 0.4524 |
| 0.224 | 7.0 | 343 | 0.3581 | 0.8488 | 0.8461 | 0.8477 | 0.5578 | 0.1523 | 0.7373 | 0.4422 |
| 0.2335 | 8.0 | 392 | 0.3622 | 0.8532 | 0.8510 | 0.8502 | 0.5656 | 0.1497 | 0.7440 | 0.4344 |
| 0.2453 | 9.0 | 441 | 0.3552 | 0.8573 | 0.8560 | 0.8554 | 0.5758 | 0.1446 | 0.7503 | 0.4242 |
| 0.2194 | 10.0 | 490 | 0.3577 | 0.8555 | 0.8534 | 0.8534 | 0.5733 | 0.1465 | 0.7475 | 0.4267 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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