---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: bart-base-facebook
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: train
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.7146
---

<!-- 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-facebook

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1877
- Rouge1: 0.7146
- Rouge2: 0.3305
- Rougel: 0.2988
- Rougelsum: 0.6822

## 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: 10
- eval_batch_size: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.505         | 1.0   | 1359 | 2.1048          | 0.6788 | 0.3022 | 0.2843 | 0.6497    |
| 2.0216        | 2.0   | 2718 | 2.1010          | 0.7022 | 0.3182 | 0.2974 | 0.672     |
| 1.7088        | 3.0   | 4077 | 2.1228          | 0.7048 | 0.3214 | 0.2968 | 0.6722    |
| 1.4778        | 4.0   | 5436 | 2.1655          | 0.7117 | 0.325  | 0.2984 | 0.6786    |
| 1.3161        | 5.0   | 6795 | 2.1877          | 0.7146 | 0.3305 | 0.2988 | 0.6822    |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1