---
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: 0.0451
- Rouge1: 50.5384
- Rouge2: 38.354
- Rougel: 39.3824
- Rougelsum: 39.3274

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.4522        | 1.0   | 29   | 0.1016          | 39.3219 | 23.9312 | 30.059  | 30.0842   |
| 0.115         | 2.0   | 58   | 0.0910          | 42.5308 | 28.0438 | 34.7355 | 34.6854   |
| 0.1008        | 3.0   | 87   | 0.0773          | 46.8072 | 32.1794 | 38.8917 | 39.1092   |
| 0.0887        | 4.0   | 116  | 0.0748          | 40.6291 | 27.6322 | 31.1978 | 31.2266   |
| 0.0878        | 5.0   | 145  | 0.0678          | 45.3986 | 31.5703 | 35.6892 | 35.7214   |
| 0.077         | 6.0   | 174  | 0.0598          | 47.8845 | 34.9979 | 39.1758 | 39.3253   |
| 0.0714        | 7.0   | 203  | 0.0559          | 49.0723 | 35.9285 | 37.1426 | 37.1948   |
| 0.061         | 8.0   | 232  | 0.0509          | 49.7851 | 37.3486 | 40.8669 | 40.9567   |
| 0.0625        | 9.0   | 261  | 0.0465          | 50.7533 | 37.6276 | 39.9594 | 40.0946   |
| 0.0488        | 10.0  | 290  | 0.0451          | 50.5384 | 38.354  | 39.3824 | 39.3274   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1