---
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-scope-summarization
  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-large-cnn-finetuned-scope-summarization

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: 0.1120
- Rouge1: 51.232
- Rouge2: 37.3103
- Rougel: 39.2783
- Rougelsum: 39.2011

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.6379        | 1.0   | 40   | 0.2289          | 45.9991 | 29.5151 | 34.3864 | 34.3984   |
| 0.2731        | 2.0   | 80   | 0.1935          | 47.3991 | 33.1933 | 38.1538 | 38.0514   |
| 0.2362        | 3.0   | 120  | 0.1734          | 47.4125 | 32.2496 | 35.7852 | 35.8279   |
| 0.222         | 4.0   | 160  | 0.1665          | 46.2226 | 32.0249 | 37.016  | 36.8941   |
| 0.2005        | 5.0   | 200  | 0.1530          | 50.1647 | 35.1015 | 39.0526 | 39.0721   |
| 0.1971        | 6.0   | 240  | 0.1434          | 49.7914 | 35.5371 | 39.2372 | 39.244    |
| 0.1754        | 7.0   | 280  | 0.1286          | 49.8482 | 35.7536 | 40.2412 | 40.2248   |
| 0.1777        | 8.0   | 320  | 0.1187          | 51.6342 | 38.223  | 41.4109 | 41.3626   |
| 0.1555        | 9.0   | 360  | 0.1149          | 49.1858 | 36.1404 | 38.857  | 38.7268   |
| 0.1415        | 10.0  | 400  | 0.1120          | 51.232  | 37.3103 | 39.2783 | 39.2011   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1