---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-newsroom
model-index:
- name: pegasus-newsroom-headline_writer_57k
  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-headline_writer_57k

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: 1.3599
- Rouge1: 42.2586
- Rouge2: 23.2731
- Rougel: 35.8685
- Rougelsum: 36.0581
- Gen Len: 34.3651

## 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: 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.5213        | 1.0   | 5670  | 1.4040          | 41.8648 | 22.8205 | 35.3983 | 35.535    | 34.8817 |
| 1.4171        | 2.0   | 11340 | 1.3672          | 42.26   | 23.2611 | 35.8016 | 35.9753   | 34.3492 |
| 1.3722        | 3.0   | 17010 | 1.3599          | 42.2586 | 23.2731 | 35.8685 | 36.0581   | 34.3651 |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.0
- Tokenizers 0.13.1