---
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: punjabi-muril-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-muril-ner

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0654
- Precision: 0.7923
- Recall: 0.8113
- F1: 0.8017
- Accuracy: 0.9859

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3366        | 1.0   | 1613  | 0.2698          | 0.0       | 0.0    | 0.0    | 0.9551   |
| 0.1552        | 2.0   | 3226  | 0.1180          | 0.7114    | 0.4972 | 0.5853 | 0.9763   |
| 0.0959        | 3.0   | 4839  | 0.0904          | 0.7262    | 0.7161 | 0.7211 | 0.9829   |
| 0.0708        | 4.0   | 6452  | 0.0751          | 0.7679    | 0.7498 | 0.7587 | 0.9840   |
| 0.0474        | 5.0   | 8065  | 0.0672          | 0.7907    | 0.7731 | 0.7818 | 0.9854   |
| 0.0367        | 6.0   | 9678  | 0.0627          | 0.7870    | 0.8045 | 0.7957 | 0.9856   |
| 0.0308        | 7.0   | 11291 | 0.0598          | 0.7942    | 0.7915 | 0.7928 | 0.9859   |
| 0.0247        | 8.0   | 12904 | 0.0612          | 0.7891    | 0.8123 | 0.8005 | 0.9860   |
| 0.0202        | 9.0   | 14517 | 0.0666          | 0.8015    | 0.8015 | 0.8015 | 0.9860   |
| 0.0181        | 10.0  | 16130 | 0.0654          | 0.7923    | 0.8113 | 0.8017 | 0.9859   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1