---
license: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- aihub_paper_summarization
metrics:
- rouge
model-index:
- name: pko-t5-small-finetuned-paper-4564652
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: aihub_paper_summarization
      type: aihub_paper_summarization
      config: default
      split: train
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 4.874
---

<!-- 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. -->

# pko-t5-small-finetuned-paper-4564652

This model is a fine-tuned version of [paust/pko-t5-small](https://huggingface.co/paust/pko-t5-small) on the aihub_paper_summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4922
- Rouge1: 4.874
- Rouge2: 1.0497
- Rougel: 4.8599
- Rougelsum: 4.854
- Gen Len: 18.9953

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2