---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: bart-base-finetuned-xsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: train[:10%]
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 35.8214
pipeline_tag: summarization
---

<!-- 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-xsum

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: 1.9356
- Rouge1: 35.8214
- Rouge2: 14.7565
- Rougel: 29.4566
- Rougelsum: 29.4496
- Gen Len: 19.562

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.301         | 1.0   | 1148 | 1.9684          | 34.4715 | 13.6638 | 28.1147 | 28.1204   | 19.5816 |
| 2.1197        | 2.0   | 2296 | 1.9442          | 35.2502 | 14.284  | 28.8462 | 28.8384   | 19.5546 |
| 1.9804        | 3.0   | 3444 | 1.9406          | 35.7799 | 14.7422 | 29.3669 | 29.3742   | 19.5326 |
| 1.8891        | 4.0   | 4592 | 1.9349          | 35.5151 | 14.4668 | 29.0359 | 29.0484   | 19.5492 |
| 1.827         | 5.0   | 5740 | 1.9356          | 35.8214 | 14.7565 | 29.4566 | 29.4496   | 19.562  |


### Framework versions

- Transformers 4.40.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.0
- Tokenizers 0.19.1