---
library_name: transformers
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: legal-bert-Federal-Regulations
  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. -->

# legal-bert-Federal-Regulations

This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6277
- Accuracy: 0.7154
- Precision: 0.7483
- Recall: 0.7154
- F1: 0.7248
- Roc Auc: 0.7853
- Confusion Matrix: [[2451, 934], [445, 1016]]

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc | Confusion Matrix            |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|:---------------------------:|
| 0.606         | 1.0   | 600  | 0.6376          | 0.6605   | 0.7333    | 0.6605 | 0.6745 | 0.7564  | [[2110, 1275], [370, 1091]] |
| 0.5312        | 2.0   | 1200 | 0.5504          | 0.7418   | 0.7473    | 0.7418 | 0.7442 | 0.7829  | [[2708, 677], [574, 887]]   |
| 0.4563        | 3.0   | 1800 | 0.6277          | 0.7154   | 0.7483    | 0.7154 | 0.7248 | 0.7853  | [[2451, 934], [445, 1016]]  |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1