metadata

tags:
  - paraphrasing
  - generated_from_trainer
datasets:
  - paws
metrics:
  - rouge
model-index:
  - name: pegasus-xsum-finetuned-paws
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: paws
          type: paws
          args: labeled_final
        metrics:
          - name: Rouge1
            type: rouge
            value: 92.4371

pegasus-xsum-finetuned-paws

This model is a fine-tuned version of google/pegasus-xsum on the paws dataset. It achieves the following results on the evaluation set:

Loss: 2.1199
Rouge1: 92.4371
Rouge2: 75.4061
Rougel: 84.1519
Rougelsum: 84.1958

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: 32
eval_batch_size: 16
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
2.1481	1.46	1000	2.0112	93.7727	73.3021	84.2963	84.2506
2.0113	2.93	2000	2.0579	93.813	73.4119	84.3674	84.2693
2.054	4.39	3000	2.0890	93.3926	73.3727	84.2814	84.1649

Framework versions

Transformers 4.18.0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1