---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: PEGASUS_CNNDM_ORIGIN
  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_CNNDM_ORIGIN

This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co./google/pegasus-cnn_dailymail) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7525
- Rouge1: 0.3585
- Rouge2: 0.1596
- Rougel: 0.2651
- Rougelsum: 0.2651
- Gen Len: 57.9427
- Precision: 0.8769
- Recall: 0.8915
- F1: 0.884

## 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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
| 1.0026        | 1.0   | 625  | 1.7480          | 0.3556 | 0.1565 | 0.2627 | 0.2629    | 57.9482 | 0.8764    | 0.8909 | 0.8835 |
| 0.9045        | 2.0   | 1250 | 1.7525          | 0.3585 | 0.1596 | 0.2651 | 0.2651    | 57.9427 | 0.8769    | 0.8915 | 0.884  |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0