transformers pytorch tensorboard bart text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: bart-base-finetuned-multi-news
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bart-base-finetuned-multi-news

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: 2.6353
- Rouge1: 15.1146
- Rouge2: 5.3873
- Rougel: 11.4132
- Rougelsum: 13.2739

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.9189        | 1.0   | 625  | 2.4645          | 15.2063 | 5.2852 | 11.5864 | 13.4208   |
| 2.4697        | 2.0   | 1250 | 2.4706          | 15.3737 | 5.4725 | 11.7465 | 13.5681   |
| 2.1831        | 3.0   | 1875 | 2.4789          | 14.8306 | 5.0857 | 11.2416 | 13.1072   |
| 1.9598        | 4.0   | 2500 | 2.5299          | 15.1744 | 5.5465 | 11.6445 | 13.4053   |
| 1.7777        | 5.0   | 3125 | 2.5799          | 14.9417 | 5.2124 | 11.3553 | 13.1401   |
| 1.6454        | 6.0   | 3750 | 2.6028          | 14.9804 | 5.333  | 11.294  | 13.2385   |
| 1.554         | 7.0   | 4375 | 2.6353          | 15.1146 | 5.3873 | 11.4132 | 13.2739   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
