---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-cnn_dailymail
  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-large-finetuned-cnn_dailymail

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8591
- Rouge1: 47.5545
- Rouge2: 24.7124
- Rougel: 34.1029
- Rougelsum: 44.0189
- Bleu 1: 37.0636
- Bleu 2: 25.5604
- Bleu 3: 19.3415
- Meteor: 38.0261
- Lungime rezumat: 57.9183
- Lungime original: 48.6393

## 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: 5.6e-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: 4

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu 1  | Bleu 2  | Bleu 3  | Meteor  | Lungime rezumat | Lungime original |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:---------------:|:----------------:|
| 0.9693        | 1.0   | 28660  | 0.8691          | 47.0692 | 24.3586 | 33.6526 | 43.4825   | 36.2858 | 24.9738 | 18.8926 | 37.8237 | 59.475          | 48.6393          |
| 0.8248        | 2.0   | 57320  | 0.8598          | 46.751  | 24.0748 | 33.3009 | 43.1207   | 36.0845 | 24.7477 | 18.6962 | 37.8529 | 60.7557         | 48.6393          |
| 0.7578        | 3.0   | 85980  | 0.8570          | 47.2636 | 24.4414 | 33.8604 | 43.6832   | 36.6893 | 25.2309 | 19.0981 | 38.0561 | 59.0953         | 48.6393          |
| 0.7145        | 4.0   | 114640 | 0.8591          | 47.5545 | 24.7124 | 34.1029 | 44.0189   | 37.0636 | 25.5604 | 19.3415 | 38.0261 | 57.9183         | 48.6393          |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1