---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: bart-base-multi-news
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: multi_news
      type: multi_news
      config: train
      split: validation
      args: train
    metrics:
    - name: Rouge1
      type: rouge
      value: 27.57
---

<!-- 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-multi-news

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9167
- Rouge1: 27.57
- Rouge2: 8.53
- Rougel: 15.17
- Rougelsum: 18.03

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.8539        | 1.0   | 1250  | 2.5026          | 27.57  | 8.53   | 15.17  | 18.03     |
| 2.3547        | 2.0   | 2500  | 2.5102          | 27.57  | 8.53   | 15.17  | 18.03     |
| 2.0079        | 3.0   | 3750  | 2.5593          | 27.57  | 8.53   | 15.17  | 18.03     |
| 1.7303        | 4.0   | 5000  | 2.6260          | 27.57  | 8.53   | 15.17  | 18.03     |
| 1.4993        | 5.0   | 6250  | 2.7184          | 27.57  | 8.53   | 15.17  | 18.03     |
| 1.3136        | 6.0   | 7500  | 2.8246          | 27.57  | 8.53   | 15.17  | 18.03     |
| 1.1718        | 7.0   | 8750  | 2.8684          | 27.57  | 8.53   | 15.17  | 18.03     |
| 1.0729        | 8.0   | 10000 | 2.9167          | 27.57  | 8.53   | 15.17  | 18.03     |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3