---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: multi-news-diff-weight
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: multi_news
      type: multi_news
      config: default
      split: train[:95%]
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 9.815
---

<!-- 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. -->

# multi-news-diff-weight

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: 2.3427
- Rouge1: 9.815
- Rouge2: 3.8774
- Rougel: 7.6169
- Rougelsum: 8.9863

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.75          | 1.0   | 19225 | 2.4494          | 9.5021 | 3.5429 | 7.3531 | 8.6912    |
| 2.456         | 2.0   | 38450 | 2.3665          | 9.8103 | 3.8494 | 7.6256 | 8.9991    |
| 2.285         | 3.0   | 57675 | 2.3427          | 9.815  | 3.8774 | 7.6169 | 8.9863    |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3