transformers pytorch tensorboard pegasus_x text2text-generation summarization generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: pegasus-x-large-finetuned-summarization
  results: []
---

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# pegasus-x-large-finetuned-summarization

This model is a fine-tuned version of [google/pegasus-x-large](https://huggingface.co/google/pegasus-x-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9503
- Rouge1: 54.656
- Rouge2: 33.2773
- Rougel: 44.7797
- Rougelsum: 51.2888

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.1821        | 1.0   | 308  | 0.9389          | 49.6848 | 29.0753 | 40.9828 | 47.1619   |
| 0.8932        | 2.0   | 616  | 0.8955          | 49.6176 | 28.8588 | 41.7149 | 47.3719   |
| 0.7433        | 3.0   | 924  | 0.9202          | 54.0016 | 31.8254 | 43.4441 | 50.9312   |
| 0.6495        | 4.0   | 1232 | 0.9321          | 52.6912 | 31.6843 | 43.8896 | 49.8726   |
| 0.587         | 5.0   | 1540 | 0.9503          | 54.656  | 33.2773 | 44.7797 | 51.2888   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
