---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-CNN-DailyNews
  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-finetuned-CNN-DailyNews

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8665
- Rouge1: 0.1884
- Rouge2: 0.1059
- Rougel: 0.1664
- Rougelsum: 0.1772

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6095        | 1.0   | 63   | 1.9725          | 0.1592 | 0.0879 | 0.1436 | 0.1489    |
| 2.0568        | 2.0   | 126  | 1.8743          | 0.1945 | 0.1119 | 0.1714 | 0.1827    |
| 1.7918        | 3.0   | 189  | 1.8428          | 0.1867 | 0.1053 | 0.1638 | 0.1734    |
| 1.6358        | 4.0   | 252  | 1.8366          | 0.1873 | 0.1081 | 0.1664 | 0.1758    |
| 1.4646        | 5.0   | 315  | 1.8587          | 0.1915 | 0.1075 | 0.1684 | 0.1786    |
| 1.3943        | 6.0   | 378  | 1.8478          | 0.1824 | 0.1056 | 0.1619 | 0.1706    |
| 1.2954        | 7.0   | 441  | 1.8752          | 0.1897 | 0.1079 | 0.1662 | 0.1764    |
| 1.2544        | 8.0   | 504  | 1.8665          | 0.1884 | 0.1059 | 0.1664 | 0.1772    |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1