---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: punjabi-bert-ner
  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. -->

# punjabi-bert-ner

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an [punjabi-ner](https://huggingface.co/datasets/mirfan899/punjabi-ner) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0773
- Precision: 0.7730
- Recall: 0.7767
- F1: 0.7748
- Accuracy: 0.9794

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1001        | 1.0   | 1613 | 0.0792          | 0.7619    | 0.6539 | 0.7037 | 0.9752   |
| 0.0645        | 2.0   | 3226 | 0.0742          | 0.7684    | 0.7528 | 0.7605 | 0.9787   |
| 0.0397        | 3.0   | 4839 | 0.0773          | 0.7730    | 0.7767 | 0.7748 | 0.9794   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3