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

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: 0.3634
- Rouge1: 0.2438
- Rouge2: 0.201
- Rougel: 0.232
- Rougelsum: 0.2319

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.7832        | 1.0   | 157  | 0.4721          | 0.229  | 0.18   | 0.2151 | 0.2149    |
| 0.4617        | 2.0   | 314  | 0.4217          | 0.2426 | 0.1997 | 0.2312 | 0.2313    |
| 0.3798        | 3.0   | 471  | 0.3847          | 0.2435 | 0.2004 | 0.2312 | 0.2314    |
| 0.3252        | 4.0   | 628  | 0.3781          | 0.2499 | 0.2078 | 0.2385 | 0.2384    |
| 0.2857        | 5.0   | 785  | 0.3631          | 0.2418 | 0.1994 | 0.2314 | 0.2313    |
| 0.2616        | 6.0   | 942  | 0.3563          | 0.2448 | 0.201  | 0.2329 | 0.2331    |
| 0.2348        | 7.0   | 1099 | 0.3623          | 0.243  | 0.1984 | 0.2313 | 0.2311    |
| 0.2183        | 8.0   | 1256 | 0.3634          | 0.2438 | 0.201  | 0.232  | 0.2319    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0