---
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: 1.8242
- Rouge1: 0.4168
- Rouge2: 0.1843
- Rougel: 0.26
- Rougelsum: 0.2614
- Gen Len: 126.1232

## 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-06
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| No log        | 0.9889 | 67   | 2.0691          | 0.3965 | 0.1608 | 0.2317 | 0.2325    | 134.8522 |
| No log        | 1.9926 | 135  | 1.9581          | 0.4184 | 0.1826 | 0.2539 | 0.255     | 133.4433 |
| No log        | 2.9963 | 203  | 1.9041          | 0.4129 | 0.1792 | 0.2554 | 0.2563    | 127.0591 |
| No log        | 4.0    | 271  | 1.8745          | 0.4111 | 0.1769 | 0.2579 | 0.2586    | 126.7635 |
| No log        | 4.9889 | 338  | 1.8539          | 0.4122 | 0.1754 | 0.258  | 0.2586    | 126.0542 |
| No log        | 5.9926 | 406  | 1.8414          | 0.4197 | 0.1806 | 0.2603 | 0.2613    | 130.8177 |
| No log        | 6.9963 | 474  | 1.8334          | 0.4058 | 0.1712 | 0.2532 | 0.2539    | 126.1281 |
| 1.9669        | 8.0    | 542  | 1.8284          | 0.4129 | 0.1818 | 0.2587 | 0.2596    | 125.798  |
| 1.9669        | 8.9889 | 609  | 1.8246          | 0.4129 | 0.1802 | 0.257  | 0.2582    | 126.6158 |
| 1.9669        | 9.8893 | 670  | 1.8242          | 0.4168 | 0.1843 | 0.26   | 0.2614    | 126.1232 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1