---
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
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# 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: 0.5155
- Rouge1: 53.2323
- Rouge2: 38.6836
- Rougel: 41.8756
- Rougelsum: 50.7526
- Bleu 1: 39.2946
- Bleu 2: 33.2337
- Bleu 3: 30.2125
- Meteor: 40.4525
- Compression rate: 1.4202

## 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu 1  | Bleu 2  | Bleu 3  | Meteor  | Compression rate |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:----------------:|
| 1.1676        | 1.0   | 5000  | 0.4626          | 58.2243 | 46.8729 | 49.6754 | 56.3425   | 45.8036 | 41.0494 | 38.8167 | 47.5864 | 1.3223           |
| 0.8474        | 2.0   | 10000 | 0.4951          | 51.7813 | 37.5081 | 40.999  | 49.3373   | 38.9702 | 32.8144 | 30.0222 | 39.7542 | 1.3725           |
| 0.7632        | 3.0   | 15000 | 0.4712          | 54.9872 | 41.6279 | 44.557  | 52.6927   | 42.0867 | 36.3443 | 33.5877 | 43.0071 | 1.3649           |
| 0.7009        | 4.0   | 20000 | 0.4875          | 54.5016 | 40.85   | 44.0557 | 52.0705   | 40.2939 | 34.6751 | 31.8994 | 41.8203 | 1.4397           |
| 0.6563        | 5.0   | 25000 | 0.5036          | 52.3997 | 37.6472 | 41.0743 | 49.8349   | 38.2882 | 32.1617 | 29.1582 | 39.4024 | 1.441            |
| 0.6274        | 6.0   | 30000 | 0.5155          | 53.2323 | 38.6836 | 41.8756 | 50.7526   | 39.2946 | 33.2337 | 30.2125 | 40.4525 | 1.4202           |


### Framework versions

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