---
license: apache-2.0
tags:
- generated_from_trainer
- summarization
model-index:
- name: bart-base-xsum
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: xsum
      type: xsum
      config: default
      split: test
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 38.643
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 17.7546
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 32.2114
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 32.2207
      verified: true
    - name: loss
      type: loss
      value: 1.8224396705627441
      verified: true
    - name: gen_len
      type: gen_len
      value: 19.7028
      verified: true
  dataset:
    type:
      xsum: null
    name:
      xsum: null
---

<!-- 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-xsum

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on [xsum](https://huggingface.co./datasets/xsum) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8051
- R1: 0.5643
- R2: 0.3017
- Rl: 0.5427
- Rlsum: 0.5427

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | R1     | R2     | Rl     | Rlsum  |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|
| 0.8983        | 1.0   | 6377  | 0.8145          | 0.5443 | 0.2724 | 0.5212 | 0.5211 |
| 0.8211        | 2.0   | 12754 | 0.7940          | 0.5519 | 0.2831 | 0.5295 | 0.5295 |
| 0.7701        | 3.0   | 19131 | 0.7839          | 0.5569 | 0.2896 | 0.5347 | 0.5348 |
| 0.7046        | 4.0   | 25508 | 0.7792          | 0.5615 | 0.2956 | 0.5394 | 0.5393 |
| 0.6837        | 5.0   | 31885 | 0.7806          | 0.5631 | 0.2993 | 0.5416 | 0.5416 |
| 0.6412        | 6.0   | 38262 | 0.7816          | 0.5643 | 0.301  | 0.5427 | 0.5426 |
| 0.6113        | 7.0   | 44639 | 0.7881          | 0.5645 | 0.3017 | 0.5428 | 0.5428 |
| 0.5855        | 8.0   | 51016 | 0.7921          | 0.5651 | 0.303  | 0.5433 | 0.5432 |
| 0.5636        | 9.0   | 57393 | 0.7972          | 0.5649 | 0.3032 | 0.5433 | 0.5433 |
| 0.5482        | 10.0  | 63770 | 0.7996          | 0.565  | 0.3036 | 0.5436 | 0.5435 |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6