---
library_name: transformers
license: mit
base_model: sagorsarker/bangla-bert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bangla-bert-base-finetuned-ner-generated_data
  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. -->

# bangla-bert-base-finetuned-ner-generated_data

This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4845
- Precision: 0.7016
- Recall: 0.6578
- F1: 0.6790
- Accuracy: 0.8859

## 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: 50
- eval_batch_size: 50
- 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 353  | 0.4879          | 0.6705    | 0.5821 | 0.6232 | 0.8735   |
| 0.4957        | 2.0   | 706  | 0.4439          | 0.7046    | 0.6172 | 0.6580 | 0.8855   |
| 0.3208        | 3.0   | 1059 | 0.4374          | 0.6977    | 0.6563 | 0.6764 | 0.8895   |
| 0.3208        | 4.0   | 1412 | 0.4482          | 0.7183    | 0.6470 | 0.6808 | 0.8933   |
| 0.2344        | 5.0   | 1765 | 0.4610          | 0.6920    | 0.6715 | 0.6816 | 0.8908   |
| 0.1868        | 6.0   | 2118 | 0.4703          | 0.6987    | 0.6680 | 0.6830 | 0.8917   |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2