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---
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
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