---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: bart-base-finetuned-cnn-news
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: validation
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 21.8948
---

<!-- 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-finetuned-cnn-news

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8560
- Rouge1: 21.8948
- Rouge2: 9.7157
- Rougel: 17.9348
- Rougelsum: 20.5347

## 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: 0.00056
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.7005        | 1.0   | 718  | 2.9872          | 21.7279 | 9.0406 | 17.392  | 20.0627   |
| 2.937         | 2.0   | 1436 | 2.8590          | 21.3056 | 8.5254 | 17.2338 | 20.0403   |
| 2.2642        | 3.0   | 2154 | 2.6744          | 21.277  | 9.6162 | 17.7775 | 20.1688   |
| 1.5774        | 4.0   | 2872 | 2.7020          | 21.7458 | 9.846  | 18.1649 | 20.7067   |
| 1.0174        | 5.0   | 3590 | 2.8560          | 21.8948 | 9.7157 | 17.9348 | 20.5347   |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3