| --- |
| tags: |
| - paraphrasing |
| - generated_from_trainer |
| datasets: |
| - paws |
| metrics: |
| - rouge |
| model-index: |
| - name: pegasus-pubmed-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: 56.8108 |
| --- |
| |
| <!-- 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-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 |
|
|
