---
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[:20%]
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 9.9082
---

<!-- 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: 2.5350
- Rouge1: 9.9082
- Rouge2: 3.6995
- Rougel: 7.6135
- Rougelsum: 9.0176

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.8555        | 1.0   | 4047  | 2.5846          | 9.7797 | 3.6212 | 7.5597 | 8.9387    |
| 2.5262        | 2.0   | 8094  | 2.5231          | 9.7969 | 3.5968 | 7.5592 | 8.9532    |
| 2.3195        | 3.0   | 12141 | 2.5149          | 9.83   | 3.6338 | 7.5109 | 8.9725    |
| 2.1655        | 4.0   | 16188 | 2.5188          | 9.8704 | 3.6936 | 7.6094 | 9.0336    |
| 2.055         | 5.0   | 20235 | 2.5350          | 9.9082 | 3.6995 | 7.6135 | 9.0176    |


### Framework versions

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