---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
model-index:
- name: pegasus-xsum
  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

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1676

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.2677        | 0.4   | 1000  | 0.1598          |
| 0.0619        | 0.8   | 2000  | 0.1363          |
| 0.0478        | 1.2   | 3000  | 0.1305          |
| 0.0421        | 1.6   | 4000  | 0.1298          |
| 0.0403        | 2.0   | 5000  | 0.1256          |
| 0.0328        | 2.4   | 6000  | 0.1309          |
| 0.0314        | 2.8   | 7000  | 0.1296          |
| 0.0294        | 3.2   | 8000  | 0.1381          |
| 0.0259        | 3.6   | 9000  | 0.1383          |
| 0.0251        | 4.0   | 10000 | 0.1380          |
| 0.0213        | 4.4   | 11000 | 0.1450          |
| 0.0206        | 4.8   | 12000 | 0.1427          |
| 0.0201        | 5.2   | 13000 | 0.1520          |
| 0.0189        | 5.6   | 14000 | 0.1505          |
| 0.0164        | 6.0   | 15000 | 0.1515          |
| 0.0153        | 6.4   | 16000 | 0.1594          |
| 0.0153        | 6.8   | 17000 | 0.1570          |
| 0.0149        | 7.2   | 18000 | 0.1652          |
| 0.0136        | 7.6   | 19000 | 0.1662          |
| 0.013         | 8.0   | 20000 | 0.1676          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1