---
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-xsum-clara-med
  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-xsum-clara-med

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9013
- Rouge1: 43.7595
- Rouge2: 25.7022
- Rougel: 39.6153
- Rougelsum: 39.7151

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 190  | 2.5468          | 41.6125 | 24.1264 | 37.7704 | 37.8615   |
| No log        | 2.0   | 380  | 2.3603          | 41.9598 | 24.315  | 38.1087 | 38.217    |
| 2.7787        | 3.0   | 570  | 2.2604          | 42.0463 | 24.5067 | 38.1632 | 38.2716   |
| 2.7787        | 4.0   | 760  | 2.1846          | 42.1471 | 24.639  | 38.3677 | 38.471    |
| 2.2691        | 5.0   | 950  | 2.1361          | 42.4562 | 24.8962 | 38.6107 | 38.7065   |
| 2.2691        | 6.0   | 1140 | 2.0887          | 42.6005 | 24.947  | 38.7049 | 38.805    |
| 2.2691        | 7.0   | 1330 | 2.0617          | 42.7946 | 24.9509 | 38.9123 | 39.0003   |
| 2.0313        | 8.0   | 1520 | 2.0222          | 43.0201 | 25.3552 | 39.151  | 39.266    |
| 2.0313        | 9.0   | 1710 | 2.0049          | 43.2293 | 25.4719 | 39.4239 | 39.4944   |
| 1.872         | 10.0  | 1900 | 1.9899          | 43.2629 | 25.5285 | 39.4124 | 39.4591   |
| 1.872         | 11.0  | 2090 | 1.9772          | 43.4294 | 25.8006 | 39.5863 | 39.6726   |
| 1.872         | 12.0  | 2280 | 1.9630          | 43.63   | 25.7259 | 39.5521 | 39.6888   |
| 1.7497        | 13.0  | 2470 | 1.9513          | 43.4053 | 25.5567 | 39.4567 | 39.5918   |
| 1.7497        | 14.0  | 2660 | 1.9336          | 43.2584 | 25.4554 | 39.2917 | 39.3944   |
| 1.6609        | 15.0  | 2850 | 1.9345          | 43.2644 | 25.5958 | 39.3474 | 39.4645   |
| 1.6609        | 16.0  | 3040 | 1.9152          | 43.4404 | 25.6127 | 39.4472 | 39.5418   |
| 1.6609        | 17.0  | 3230 | 1.9106          | 43.2751 | 25.3213 | 39.2723 | 39.3871   |
| 1.5809        | 18.0  | 3420 | 1.9125          | 43.2335 | 25.341  | 39.2705 | 39.3577   |
| 1.5809        | 19.0  | 3610 | 1.9086          | 43.1679 | 25.3275 | 39.1858 | 39.303    |
| 1.5221        | 20.0  | 3800 | 1.9030          | 43.2794 | 25.4126 | 39.2902 | 39.4092   |
| 1.5221        | 21.0  | 3990 | 1.8996          | 43.1731 | 25.3819 | 39.1873 | 39.3172   |
| 1.5221        | 22.0  | 4180 | 1.9006          | 43.4949 | 25.4485 | 39.3092 | 39.4516   |
| 1.4714        | 23.0  | 4370 | 1.8977          | 43.5657 | 25.5974 | 39.4489 | 39.5257   |
| 1.4714        | 24.0  | 4560 | 1.9035          | 43.6444 | 25.6794 | 39.5809 | 39.683    |
| 1.4421        | 25.0  | 4750 | 1.9000          | 43.4825 | 25.5898 | 39.4319 | 39.4973   |
| 1.4421        | 26.0  | 4940 | 1.9030          | 43.4623 | 25.5726 | 39.461  | 39.6009   |
| 1.4421        | 27.0  | 5130 | 1.8993          | 43.3357 | 25.5518 | 39.3897 | 39.4672   |
| 1.4139        | 28.0  | 5320 | 1.9009          | 43.5834 | 25.7211 | 39.584  | 39.6725   |
| 1.4139        | 29.0  | 5510 | 1.9002          | 43.7115 | 25.6997 | 39.6603 | 39.7621   |
| 1.4016        | 30.0  | 5700 | 1.9013          | 43.7595 | 25.7022 | 39.6153 | 39.7151   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1