---
tags:
- generated_from_trainer
datasets:
- reddit
metrics:
- rouge
model-index:
- name: pegasus-xsum-reddit-clean-4
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: reddit
      type: reddit
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 27.7525
---

<!-- 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-reddit-clean-4

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the reddit dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7697
- Rouge1: 27.7525
- Rouge2: 7.9823
- Rougel: 20.9276
- Rougelsum: 22.6678

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.0594        | 1.0   | 1906 | 2.8489          | 27.9837 | 8.0824 | 20.9135 | 22.7261   |
| 2.861         | 2.0   | 3812 | 2.7793          | 27.8298 | 8.048  | 20.8653 | 22.6781   |
| 2.7358        | 3.0   | 5718 | 2.7697          | 27.7525 | 7.9823 | 20.9276 | 22.6678   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1