---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-newsroom
model-index:
- name: pegasus-newsroom-rewriter
  results: []
---

<!-- 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-newsroom-rewriter

This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3424
- Rouge1: 46.6856
- Rouge2: 31.6377
- Rougel: 33.2741
- Rougelsum: 44.5003
- Gen Len: 126.58

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 450  | 1.4020          | 47.0593 | 32.2065 | 33.9168 | 44.901    | 126.32  |
| 1.9944        | 2.0   | 900  | 1.3567          | 46.2635 | 30.9959 | 32.933  | 44.1659   | 126.48  |
| 1.6511        | 3.0   | 1350 | 1.3449          | 46.1544 | 30.7257 | 32.693  | 43.9977   | 126.4   |
| 1.5951        | 4.0   | 1800 | 1.3424          | 46.6856 | 31.6377 | 33.2741 | 44.5003   | 126.58  |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6