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

# urdu-bert-ner

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2125
- Precision: 0.8073
- Recall: 0.8272
- F1: 0.8171
- Accuracy: 0.9592

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1593        | 1.0   | 2272  | 0.1469          | 0.7158    | 0.8005 | 0.7558 | 0.9468   |
| 0.1154        | 2.0   | 4544  | 0.1304          | 0.7720    | 0.8116 | 0.7913 | 0.9547   |
| 0.0862        | 3.0   | 6816  | 0.1381          | 0.7912    | 0.8117 | 0.8013 | 0.9557   |
| 0.0673        | 4.0   | 9088  | 0.1404          | 0.8006    | 0.8099 | 0.8052 | 0.9567   |
| 0.0515        | 5.0   | 11360 | 0.1511          | 0.8135    | 0.8063 | 0.8099 | 0.9578   |
| 0.0402        | 6.0   | 13632 | 0.1666          | 0.8030    | 0.8235 | 0.8131 | 0.9582   |
| 0.0286        | 7.0   | 15904 | 0.1848          | 0.8066    | 0.8208 | 0.8137 | 0.9579   |
| 0.022         | 8.0   | 18176 | 0.1957          | 0.8060    | 0.8226 | 0.8142 | 0.9585   |
| 0.0201        | 9.0   | 20448 | 0.2062          | 0.8022    | 0.8283 | 0.8151 | 0.9585   |
| 0.0164        | 10.0  | 22720 | 0.2125          | 0.8073    | 0.8272 | 0.8171 | 0.9592   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3