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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: 0.3670
- F1: 0.8559
- Roc Auc: 0.8534
- Accuracy: 0.5681
- Hamming Loss: 0.1465
- Jaccard Score: 0.7481
- Zero One Loss: 0.4319
## 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 | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
| 0.5656 | 1.0 | 49 | 0.5135 | 0.7799 | 0.7750 | 0.4113 | 0.2249 | 0.6392 | 0.5887 |
| 0.4157 | 2.0 | 98 | 0.4203 | 0.8359 | 0.8309 | 0.5398 | 0.1690 | 0.7181 | 0.4602 |
| 0.3652 | 3.0 | 147 | 0.3970 | 0.8507 | 0.8431 | 0.5604 | 0.1568 | 0.7401 | 0.4396 |
| 0.3096 | 4.0 | 196 | 0.3716 | 0.8530 | 0.8489 | 0.5656 | 0.1510 | 0.7437 | 0.4344 |
| 0.2674 | 5.0 | 245 | 0.3693 | 0.8521 | 0.8489 | 0.5527 | 0.1510 | 0.7423 | 0.4473 |
| 0.2709 | 6.0 | 294 | 0.3660 | 0.8532 | 0.8509 | 0.5630 | 0.1491 | 0.7439 | 0.4370 |
| 0.2208 | 7.0 | 343 | 0.3626 | 0.8550 | 0.8534 | 0.5656 | 0.1465 | 0.7467 | 0.4344 |
| 0.2388 | 8.0 | 392 | 0.3723 | 0.8573 | 0.8541 | 0.5630 | 0.1459 | 0.7503 | 0.4370 |
| 0.2466 | 9.0 | 441 | 0.3685 | 0.8562 | 0.8541 | 0.5656 | 0.1459 | 0.7486 | 0.4344 |
| 0.2187 | 10.0 | 490 | 0.3670 | 0.8559 | 0.8534 | 0.5681 | 0.1465 | 0.7481 | 0.4319 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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