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

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# 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
