---
base_model: google/pegasus-large
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
model-index:
- name: Pegasus_no_extraction_V1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Pegasus_no_extraction_V1

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the eur-lex-sum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1652

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 5.0055        | 0.9927  | 68   | 3.8532          |
| 3.5972        | 2.0     | 137  | 3.1452          |
| 3.0381        | 2.9927  | 205  | 2.6382          |
| 2.6047        | 4.0     | 274  | 2.4301          |
| 2.4507        | 4.9927  | 342  | 2.3523          |
| 2.3115        | 6.0     | 411  | 2.3044          |
| 2.2714        | 6.9927  | 479  | 2.2742          |
| 2.1854        | 8.0     | 548  | 2.2519          |
| 2.1754        | 8.9927  | 616  | 2.2373          |
| 2.1119        | 10.0    | 685  | 2.2238          |
| 2.114         | 10.9927 | 753  | 2.2155          |
| 2.0527        | 12.0    | 822  | 2.2069          |
| 2.0622        | 12.9927 | 890  | 2.2004          |
| 2.0085        | 14.0    | 959  | 2.1929          |
| 2.0133        | 14.9927 | 1027 | 2.1902          |
| 1.9695        | 16.0    | 1096 | 2.1857          |
| 1.9827        | 16.9927 | 1164 | 2.1826          |
| 1.9389        | 18.0    | 1233 | 2.1789          |
| 1.9541        | 18.9927 | 1301 | 2.1758          |
| 1.9105        | 20.0    | 1370 | 2.1749          |
| 1.9244        | 20.9927 | 1438 | 2.1731          |
| 1.8858        | 22.0    | 1507 | 2.1716          |
| 1.9028        | 22.9927 | 1575 | 2.1712          |
| 1.8625        | 24.0    | 1644 | 2.1698          |
| 1.8798        | 24.9927 | 1712 | 2.1695          |
| 1.847         | 26.0    | 1781 | 2.1678          |
| 1.8648        | 26.9927 | 1849 | 2.1698          |
| 1.8283        | 28.0    | 1918 | 2.1671          |
| 1.8517        | 28.9927 | 1986 | 2.1656          |
| 1.8166        | 30.0    | 2055 | 2.1658          |
| 1.8391        | 30.9927 | 2123 | 2.1646          |
| 1.8068        | 32.0    | 2192 | 2.1670          |
| 1.8307        | 32.9927 | 2260 | 2.1654          |
| 1.7956        | 34.0    | 2329 | 2.1656          |
| 1.8219        | 34.9927 | 2397 | 2.1647          |
| 1.7936        | 36.0    | 2466 | 2.1652          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.19.1