---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-multi_news
model-index:
- name: pegasus-multi_news-malay_headlines_02
  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-multi_news-malay_headlines_02

This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9295
- Rouge1: 39.9859
- Rouge2: 20.1943
- Rougel: 36.1927
- Rougelsum: 36.2105
- Gen Len: 35.6062

## 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.0943        | 1.0   | 53582 | 1.9295          | 39.9859 | 20.1943 | 36.1927 | 36.2105   | 35.6062 |


### Framework versions

- Transformers 4.12.3
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3