---
library_name: transformers
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
model-index:
- name: pegasus-xsum-finetuned-cnn
  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-xsum-finetuned-cnn

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.6115
- eval_rouge1: 41.1875
- eval_rouge2: 19.2632
- eval_rougeL: 28.8605
- eval_rougeLsum: 37.8906
- eval_gen_len: 59.36
- eval_runtime: 887.2653
- eval_samples_per_second: 1.127
- eval_steps_per_second: 0.282
- epoch: 2.0
- step: 4000

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1