---
library_name: transformers
base_model: csebuetnlp/banglabert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: MediBool-banglabert-Context_Aware
  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. -->

# MediBool-banglabert-Context_Aware

This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1367
- Accuracy: 0.9882
- F1: 0.9882

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.2935        | 0.2769 | 250  | 0.2018          | 0.9763   | 0.9763 |
| 0.1594        | 0.5537 | 500  | 0.1717          | 0.9776   | 0.9776 |
| 0.1662        | 0.8306 | 750  | 0.1184          | 0.9844   | 0.9844 |
| 0.0709        | 1.1074 | 1000 | 0.1548          | 0.9844   | 0.9844 |
| 0.0810        | 1.3843 | 1250 | 0.1246          | 0.9857   | 0.9857 |
| 0.0799        | 1.6611 | 1500 | 0.1152          | 0.9863   | 0.9863 |
| 0.0720        | 1.9380 | 1750 | 0.1242          | 0.9869   | 0.9869 |
| 0.0279        | 2.2148 | 2000 | 0.1691          | 0.9844   | 0.9844 |
| 0.0228        | 2.4917 | 2250 | 0.1072          | 0.9913   | 0.9913 |
| 0.0184        | 2.7685 | 2500 | 0.1114          | 0.9906   | 0.9906 |
| 0.0173        | 3.0454 | 2750 | 0.1519          | 0.9894   | 0.9894 |


### Framework versions

- Transformers 5.1.0
- Pytorch 2.8.0+cu126
- Datasets 4.5.0
- Tokenizers 0.22.1