transformers pytorch tensorboard pegasus text2text-generation paraphrasing generated_from_trainer dataset:paws model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- paws
metrics:
- rouge
tags:
- paraphrasing
- generated_from_trainer
model-index:
- name: pegasus-pubmed-finetuned-paws
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: paws
      type: paws
      args: labeled_final
    metrics:
    - type: rouge
      value: 56.8108
      name: Rouge1
---

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# pegasus-pubmed-finetuned-paws

This model is a fine-tuned version of [google/pegasus-pubmed](https://huggingface.co/google/pegasus-pubmed) on the paws dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5012
- Rouge1: 56.8108
- Rouge2: 36.2576
- Rougel: 51.1666
- Rougelsum: 51.2193

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 0.73  | 1000 | 3.8839          | 51.2731 | 29.8072 | 45.767  | 45.5732   |
| 4.071         | 1.47  | 2000 | 3.6459          | 52.756  | 31.9185 | 48.0092 | 48.0544   |
| 3.5467        | 2.2   | 3000 | 3.5849          | 54.8127 | 33.1959 | 49.326  | 49.4971   |
| 3.5467        | 2.93  | 4000 | 3.5267          | 55.387  | 33.9516 | 50.683  | 50.6313   |
| 3.3654        | 3.66  | 5000 | 3.5031          | 57.5279 | 35.2664 | 51.9903 | 52.258    |
| 3.2844        | 4.4   | 6000 | 3.5296          | 56.0536 | 33.395  | 50.9909 | 51.244    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
