---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Super_legal_text_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. -->

# Super_legal_text_summarizer

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8504
- Rouge1: 0.4106
- Rouge2: 0.1827
- Rougel: 0.2604
- Rougelsum: 0.2624
- Gen Len: 130.9261

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| No log        | 1.0   | 203  | 1.9295          | 0.4004 | 0.1792 | 0.2546 | 0.2562    | 123.1576 |
| No log        | 2.0   | 406  | 1.8438          | 0.4163 | 0.1886 | 0.2607 | 0.2625    | 125.9655 |
| 1.8737        | 3.0   | 609  | 1.8503          | 0.4044 | 0.1721 | 0.2498 | 0.2512    | 132.9951 |
| 1.8737        | 4.0   | 812  | 1.8504          | 0.4106 | 0.1827 | 0.2604 | 0.2624    | 130.9261 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2