---
tags:
- paraphrasing
- generated_from_trainer
datasets:
- paws
metrics:
- rouge
base_model: google/pegasus-xsum
model-index:
- name: pegasus-xsum-finetuned-paws
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: paws
      type: paws
      args: labeled_final
    metrics:
    - type: rouge
      value: 92.4371
      name: Rouge1
---

<!-- 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-xsum-finetuned-paws

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the paws dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1199
- Rouge1: 92.4371
- Rouge2: 75.4061
- Rougel: 84.1519
- Rougelsum: 84.1958

## 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: 0.0001
- train_batch_size: 32
- 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
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.1481        | 1.46  | 1000 | 2.0112          | 93.7727 | 73.3021 | 84.2963 | 84.2506   |
| 2.0113        | 2.93  | 2000 | 2.0579          | 93.813  | 73.4119 | 84.3674 | 84.2693   |
| 2.054         | 4.39  | 3000 | 2.0890          | 93.3926 | 73.3727 | 84.2814 | 84.1649   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1