---
library_name: transformers
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: 1.8960
- Rouge1: 0.197
- Rouge2: 0.116
- Rougel: 0.1733
- Rougelsum: 0.1853

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.0481        | 1.0   | 63   | 1.9149          | 0.184  | 0.1081 | 0.1652 | 0.173     |
| 1.7799        | 2.0   | 126  | 1.8636          | 0.202  | 0.1142 | 0.1774 | 0.1883    |
| 1.5662        | 3.0   | 189  | 1.8301          | 0.1937 | 0.1107 | 0.1695 | 0.1787    |
| 1.4463        | 4.0   | 252  | 1.8581          | 0.1973 | 0.1166 | 0.174  | 0.1851    |
| 1.2893        | 5.0   | 315  | 1.8600          | 0.1885 | 0.1069 | 0.166  | 0.175     |
| 1.232         | 6.0   | 378  | 1.8637          | 0.1942 | 0.1115 | 0.1704 | 0.1808    |
| 1.1332        | 7.0   | 441  | 1.8797          | 0.194  | 0.1143 | 0.1725 | 0.1823    |
| 1.1014        | 8.0   | 504  | 1.8960          | 0.197  | 0.116  | 0.1733 | 0.1853    |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0