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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: punjabi-roberta-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-roberta-ner
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an [punjabi-ner](https://huggingface.co/datasets/mirfan899/punjabi-ner) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0638
- Precision: 0.7625
- Recall: 0.7844
- F1: 0.7733
- Accuracy: 0.9830
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1017 | 1.0 | 1613 | 0.0739 | 0.7020 | 0.6731 | 0.6872 | 0.9775 |
| 0.0693 | 2.0 | 3226 | 0.0623 | 0.7695 | 0.7433 | 0.7562 | 0.9824 |
| 0.046 | 3.0 | 4839 | 0.0638 | 0.7625 | 0.7844 | 0.7733 | 0.9830 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3
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