---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-legal-summarizer
  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. -->

# bart-base-legal-summarizer

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3425
- Rouge1: 33.2731
- Rouge2: 16.5293
- Rougel: 29.1491
- Rougelsum: 29.7726
- Gen Len: 15.5

## 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: 2
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 178  | 2.4487          | 27.4622 | 10.7691 | 23.652  | 24.1204   | 15.1333 |
| No log        | 2.0   | 356  | 2.3498          | 34.4    | 17.7132 | 30.1947 | 30.5913   | 14.8222 |
| 2.2551        | 3.0   | 534  | 2.3425          | 33.2731 | 16.5293 | 29.1491 | 29.7726   | 15.5    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1