---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-CNN-DailyNews
  results: []
pipeline_tag: summarization
datasets:
- cnn_dailymail
---

<!-- 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: 0.9584
- Rouge1: 0.1977
- Rouge2: 0.1321
- Rougel: 0.1792
- Rougelsum: 0.1884

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6767        | 1.0   | 63   | 1.8911          | 0.1745 | 0.0915 | 0.1536 | 0.1644    |
| 2.0691        | 2.0   | 126  | 1.5904          | 0.1777 | 0.1003 | 0.1579 | 0.1677    |
| 1.8047        | 3.0   | 189  | 1.3652          | 0.1778 | 0.1029 | 0.1587 | 0.1663    |
| 1.6345        | 4.0   | 252  | 1.2317          | 0.1959 | 0.1226 | 0.1751 | 0.1842    |
| 1.4837        | 5.0   | 315  | 1.1099          | 0.2015 | 0.1265 | 0.1796 | 0.1911    |
| 1.3904        | 6.0   | 378  | 1.0267          | 0.2004 | 0.1278 | 0.1799 | 0.1893    |
| 1.2876        | 7.0   | 441  | 0.9788          | 0.1978 | 0.1307 | 0.1784 | 0.1878    |
| 1.2578        | 8.0   | 504  | 0.9584          | 0.1977 | 0.1321 | 0.1792 | 0.1884    |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1