---
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
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# 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: 0.4011
- F1: 0.8602
- Roc Auc: 0.8579
- Accuracy: 0.5758
- Hamming Loss: 0.1420
- Jaccard Score: 0.7547
- Zero One Loss: 0.4242

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
| 0.2462        | 1.0   | 49   | 0.3759          | 0.8582 | 0.8534  | 0.5758   | 0.1465       | 0.7516        | 0.4242        |
| 0.2099        | 2.0   | 98   | 0.3534          | 0.8656 | 0.8650  | 0.5964   | 0.1350       | 0.7630        | 0.4036        |
| 0.2067        | 3.0   | 147  | 0.3660          | 0.8613 | 0.8599  | 0.5861   | 0.1401       | 0.7564        | 0.4139        |
| 0.168         | 4.0   | 196  | 0.3672          | 0.8582 | 0.8567  | 0.5835   | 0.1433       | 0.7517        | 0.4165        |
| 0.1425        | 5.0   | 245  | 0.3745          | 0.8555 | 0.8547  | 0.5656   | 0.1452       | 0.7475        | 0.4344        |
| 0.1545        | 6.0   | 294  | 0.3894          | 0.8544 | 0.8522  | 0.5578   | 0.1478       | 0.7459        | 0.4422        |
| 0.1115        | 7.0   | 343  | 0.3995          | 0.8579 | 0.8560  | 0.5681   | 0.1440       | 0.7511        | 0.4319        |
| 0.1158        | 8.0   | 392  | 0.4054          | 0.8580 | 0.8554  | 0.5681   | 0.1446       | 0.7514        | 0.4319        |
| 0.1055        | 9.0   | 441  | 0.3996          | 0.8575 | 0.8560  | 0.5681   | 0.1440       | 0.7506        | 0.4319        |
| 0.105         | 10.0  | 490  | 0.4011          | 0.8602 | 0.8579  | 0.5758   | 0.1420       | 0.7547        | 0.4242        |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1