---
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