---
license: mit
base_model: khalidrajan/roberta-base_legal_ner_finetuned
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta_crf_ner_finetuned
  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. -->

# roberta_crf_ner_finetuned

This model is a fine-tuned version of [khalidrajan/roberta-base_legal_ner_finetuned](https://huggingface.co/khalidrajan/roberta-base_legal_ner_finetuned) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 45.0197
- Precision: 0.7445
- Recall: 0.7491
- F1: 0.7458
- Accuracy: 0.9569

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 35.5086       | 1.0   | 340  | 47.8493         | 0.5897    | 0.6128 | 0.5997 | 0.9460   |
| 29.9206       | 2.0   | 680  | 44.2660         | 0.6897    | 0.7258 | 0.7067 | 0.9548   |
| 26.0727       | 3.0   | 1020 | 45.0197         | 0.7445    | 0.7491 | 0.7458 | 0.9569   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1