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---
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: 1.8682
- Rouge1: 0.184
- Rouge2: 0.1067
- Rougel: 0.1628
- Rougelsum: 0.1718

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6113        | 1.0   | 63   | 1.9753          | 0.1612 | 0.092  | 0.146  | 0.1524    |
| 2.0604        | 2.0   | 126  | 1.8843          | 0.1922 | 0.1126 | 0.1709 | 0.1824    |
| 1.7829        | 3.0   | 189  | 1.8400          | 0.1874 | 0.1056 | 0.1672 | 0.1754    |
| 1.6337        | 4.0   | 252  | 1.8325          | 0.1878 | 0.1079 | 0.1664 | 0.176     |
| 1.4657        | 5.0   | 315  | 1.8439          | 0.1839 | 0.1057 | 0.1651 | 0.1719    |
| 1.3926        | 6.0   | 378  | 1.8445          | 0.1868 | 0.1049 | 0.1657 | 0.1752    |
| 1.2903        | 7.0   | 441  | 1.8545          | 0.1878 | 0.1072 | 0.1663 | 0.1753    |
| 1.2512        | 8.0   | 504  | 1.8682          | 0.184  | 0.1067 | 0.1628 | 0.1718    |


### Framework versions

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