---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-cnn_dailymail-finetuned-scope-summarization
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pegasus-cnn_dailymail-finetuned-scope-summarization

This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1923
- Rouge1: 56.9116
- Rouge2: 45.4236
- Rougel: 49.8645
- Rougelsum: 49.71

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.5864        | 1.0   | 158  | 0.3056          | 41.1501 | 21.8098 | 34.2505 | 34.2057   |
| 0.3517        | 2.0   | 316  | 0.2787          | 45.9535 | 26.9084 | 37.7287 | 37.7213   |
| 0.2835        | 3.0   | 474  | 0.2655          | 49.4653 | 30.6584 | 40.5201 | 40.4494   |
| 0.2683        | 4.0   | 632  | 0.2528          | 50.2066 | 32.8862 | 40.4058 | 40.2244   |
| 0.2557        | 5.0   | 790  | 0.2469          | 50.3451 | 33.536  | 41.7433 | 41.6118   |
| 0.2493        | 6.0   | 948  | 0.2382          | 51.9053 | 36.1533 | 42.0343 | 41.8884   |
| 0.2406        | 7.0   | 1106 | 0.2330          | 53.2105 | 38.1    | 43.434  | 43.2194   |
| 0.235         | 8.0   | 1264 | 0.2267          | 51.9642 | 38.1903 | 44.4502 | 44.3851   |
| 0.2296        | 9.0   | 1422 | 0.2237          | 53.5609 | 38.9875 | 44.7145 | 44.6146   |
| 0.2246        | 10.0  | 1580 | 0.2195          | 54.6691 | 41.5464 | 45.7506 | 45.6856   |
| 0.221         | 11.0  | 1738 | 0.2141          | 54.4114 | 41.2748 | 45.9992 | 45.8182   |
| 0.2145        | 12.0  | 1896 | 0.2097          | 55.3852 | 42.9342 | 48.376  | 48.5267   |
| 0.2115        | 13.0  | 2054 | 0.2060          | 55.9251 | 43.4806 | 48.0303 | 47.9584   |
| 0.2081        | 14.0  | 2212 | 0.2017          | 55.8426 | 43.1239 | 47.8006 | 47.8356   |
| 0.2042        | 15.0  | 2370 | 0.1997          | 55.4631 | 42.78   | 47.307  | 47.3142   |
| 0.2031        | 16.0  | 2528 | 0.1970          | 57.0004 | 44.4252 | 49.6236 | 49.5213   |
| 0.1996        | 17.0  | 2686 | 0.1953          | 55.438  | 43.8797 | 48.536  | 48.3506   |
| 0.1991        | 18.0  | 2844 | 0.1939          | 56.1102 | 44.5176 | 48.5553 | 48.4163   |
| 0.1963        | 19.0  | 3002 | 0.1925          | 56.6366 | 45.3753 | 49.4421 | 49.3468   |
| 0.1955        | 20.0  | 3160 | 0.1923          | 56.9116 | 45.4236 | 49.8645 | 49.71     |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1