---
license: mit
base_model: sagorsarker/bangla-bert-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bangla-bert-base-MLTC-1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bangla-bert-base-MLTC-1

This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3627
- F1: 0.8553
- Roc Auc: 0.8521
- Accuracy: 0.5707
- Hamming Loss: 0.1478
- Jaccard Score: 0.7473
- Zero One Loss: 0.4293

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
| 0.3717        | 1.0   | 146  | 0.3740          | 0.8447 | 0.8438  | 0.5398   | 0.1562       | 0.7312        | 0.4602        |
| 0.3812        | 2.0   | 292  | 0.3627          | 0.8373 | 0.8420  | 0.5476   | 0.1581       | 0.7201        | 0.4524        |
| 0.2373        | 3.0   | 438  | 0.3830          | 0.8450 | 0.8386  | 0.5476   | 0.1613       | 0.7316        | 0.4524        |
| 0.1688        | 4.0   | 584  | 0.3610          | 0.8555 | 0.8534  | 0.5758   | 0.1465       | 0.7475        | 0.4242        |
| 0.153         | 5.0   | 730  | 0.3627          | 0.8553 | 0.8521  | 0.5707   | 0.1478       | 0.7473        | 0.4293        |


### Framework versions

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