---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BanglaHealthNER-Model
  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. -->

# BanglaHealthNER-Model

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2844
- Precision: 0.5616
- Recall: 0.6298
- F1: 0.5937
- Accuracy: 0.8980

## 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: 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2916        | 1.0   | 1590 | 0.2980          | 0.4946    | 0.5763 | 0.5323 | 0.8890   |
| 0.256         | 2.0   | 3180 | 0.2833          | 0.5443    | 0.5831 | 0.5630 | 0.8974   |
| 0.2332        | 3.0   | 4770 | 0.2768          | 0.5378    | 0.6292 | 0.5799 | 0.8991   |
| 0.1965        | 4.0   | 6360 | 0.2797          | 0.5527    | 0.6208 | 0.5848 | 0.9005   |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.21.2