---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
datasets:
- Andyrasika/TweetSumm-tuned
metrics:
- rouge
model-index:
- name: bart-large-xsum-tweetsum
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: Andyrasika/TweetSumm-tuned
      type: Andyrasika/TweetSumm-tuned
    metrics:
    - name: Rouge1
      type: rouge
      value: 46.1359
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/samuel-lima-tech4humans/peft-tweetsum/runs/8kw429vm)
# bart-large-xsum-tweetsum

This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the Andyrasika/TweetSumm-tuned dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9921
- Rouge1: 46.1359
- Rouge2: 20.5196
- Rougel: 38.6353
- Rougelsum: 41.9642
- Gen Len: 45.1

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1