---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-newsroom
model-index:
- name: pegasus-newsroom-summarizer_30216
  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-summarizer_30216

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: 0.9637
- Rouge1: 52.0929
- Rouge2: 34.6709
- Rougel: 41.1615
- Rougelsum: 48.4141
- Gen Len: 102.017

## 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: 2
- eval_batch_size: 2
- 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  |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.0592        | 1.0   | 12086 | 0.9743          | 51.6187 | 34.1687 | 40.5959 | 47.9305   | 104.3352 |
| 0.9742        | 2.0   | 24172 | 0.9647          | 52.1837 | 34.7301 | 41.2599 | 48.4955   | 101.2771 |
| 0.9371        | 3.0   | 36258 | 0.9637          | 52.0929 | 34.6709 | 41.1615 | 48.4141   | 102.017  |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1