---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-newsroom
model-index:
- name: pegasus-newsroom-headline_writer_oct22
  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_oct22

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: 1.3462
- Rouge1: 41.8799
- Rouge2: 23.1785
- Rougel: 35.5346
- Rougelsum: 35.6203
- Gen Len: 34.3108

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4364        | 1.0   | 38400  | 1.3730          | 41.9525 | 23.0823 | 35.5435 | 35.6485   | 34.1161 |
| 1.2483        | 2.0   | 76800  | 1.3430          | 42.1538 | 23.3302 | 35.8119 | 35.9063   | 33.9333 |
| 1.1873        | 3.0   | 115200 | 1.3462          | 41.8799 | 23.1785 | 35.5346 | 35.6203   | 34.3108 |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1