---
base_model: google/pegasus-large
tags:
- summarization
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-scientific-articles
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: scientific_papers
      type: scientific_papers
      config: pubmed
      split: train
      args: pubmed
    metrics:
    - name: Rouge1
      type: rouge
      value: 32.8743
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pegasus-large-finetuned-scientific-articles

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4553
- Rouge1: 32.8743
- Rouge2: 10.8417
- Rougel: 20.3101
- Rougelsum: 28.3673

## 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: 2
- eval_batch_size: 2
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.0377        | 1.0   | 252  | 2.5409          | 30.5637 | 9.5168  | 18.2596 | 26.2196   |
| 2.6145        | 2.0   | 504  | 2.4722          | 31.5518 | 9.9698  | 19.9187 | 26.695    |
| 2.4322        | 3.0   | 756  | 2.4553          | 32.8743 | 10.8417 | 20.3101 | 28.3673   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1