---
base_model: google/pegasus-x-large
tags:
  - summarization
  - summary
  - booksum
  - long-document
  - long-form
datasets:
  - ubaada/booksum-complete-cleaned
language:
  - en
pipeline_tag: summarization
metrics:
  - rouge
model-index:
  - name: ubaada/pegasus-x-large-booksum-16k
    results:
      - task:
          type: summarization
          name: Summarization
        dataset:
          name: BookSum
          type: ubaada/booksum-complete-cleaned
          config: ubaada--booksum
          split: test
        metrics:
          - type: rouge
            value: 30.947853
            name: ROUGE-1
            verified: false
          - type: rouge
            value: 5.568146
            name: ROUGE-2
            verified: false
---

<!-- 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. -->

# pegasus-x-large-booksum-16k

This model is a fine-tuned version of [google/pegasus-x-large](https://huggingface.co/google/pegasus-x-large) on [ubaada/booksum-complete-cleaned](https://huggingface.co/datasets/ubaada/booksum-complete-cleaned). It was trained on the 'train' split of chapters sub-dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9677
- Rouge1: 0.3504
- Rouge2: 0.0525
- Rougel: 0.1398

## 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: 8e-05
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
| 1.417         | 0.9996 | 628  | 1.9677          | 0.3504 | 0.0525 | 0.1398 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1