---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-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-base-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: 0.2173
- Rouge1: 0.169
- Rouge2: 0.1419
- Rougel: 0.1624
- Rougelsum: 0.1651

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.0798        | 1.0   | 7    | 0.4261          | 0.1312 | 0.0749 | 0.0947 | 0.0967    |
| 0.4858        | 2.0   | 14   | 0.2775          | 0.1419 | 0.1037 | 0.1285 | 0.1288    |
| 0.3719        | 3.0   | 21   | 0.2435          | 0.16   | 0.1307 | 0.151  | 0.1523    |
| 0.298         | 4.0   | 28   | 0.2311          | 0.1619 | 0.1292 | 0.1527 | 0.1554    |
| 0.2607        | 5.0   | 35   | 0.2318          | 0.1593 | 0.1259 | 0.1493 | 0.1526    |
| 0.2276        | 6.0   | 42   | 0.2211          | 0.1566 | 0.1259 | 0.1479 | 0.151     |
| 0.2173        | 7.0   | 49   | 0.2177          | 0.169  | 0.1419 | 0.1624 | 0.1651    |
| 0.1801        | 8.0   | 56   | 0.2173          | 0.169  | 0.1419 | 0.1624 | 0.1651    |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1