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

# results

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: 0.6504
- Accuracy: 0.8201

## 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: 16
- eval_batch_size: 16
- 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
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.2063        | 0.2015 | 250  | 0.7486          | 0.7993   |
| 0.4038        | 0.4029 | 500  | 0.3953          | 0.8140   |
| 0.4264        | 0.6044 | 750  | 0.3772          | 0.8156   |
| 0.3938        | 0.8058 | 1000 | 0.3900          | 0.8146   |
| 0.393         | 1.0073 | 1250 | 0.4148          | 0.8172   |
| 0.2627        | 1.2087 | 1500 | 0.4601          | 0.8247   |
| 0.2864        | 1.4102 | 1750 | 0.4548          | 0.8185   |
| 0.2559        | 1.6116 | 2000 | 0.4390          | 0.8138   |
| 0.2607        | 1.8131 | 2250 | 0.4408          | 0.8215   |
| 0.247         | 2.0145 | 2500 | 0.4906          | 0.8241   |
| 0.1356        | 2.2160 | 2750 | 0.6311          | 0.8177   |
| 0.1462        | 2.4174 | 3000 | 0.6750          | 0.8150   |
| 0.1252        | 2.6189 | 3250 | 0.6950          | 0.8207   |
| 0.1339        | 2.8203 | 3500 | 0.6504          | 0.8201   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0