---
tags:
- generated_from_trainer
datasets:
- jsonl_dataset_sum.py
metrics:
- rouge
model-index:
- name: summarization_all
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: jsonl_dataset_sum.py
      type: jsonl_dataset_sum.py
      config: 'null'
      split: None
    metrics:
    - name: Rouge1
      type: rouge
      value: 21.7197
license: artistic-2.0
language:
- ko
---

<!-- 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. -->

# summarization_all

This model is a fine-tuned version of [KETI-AIR/long-ke-t5-base](https://huggingface.co/KETI-AIR/long-ke-t5-base) on the jsonl_dataset_sum.py dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0758
- Rouge1: 21.7197
- Rouge2: 10.1392
- Rougel: 21.1499
- Rougelsum: 21.173
- Gen Len: 87.4589

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.2171        | 1.0   | 184670 | 1.2070          | 20.611  | 9.2868  | 20.0833 | 20.1095   | 87.4065 |
| 1.0916        | 2.0   | 369340 | 1.1190          | 21.3264 | 9.8656  | 20.7683 | 20.8005   | 88.0284 |
| 0.9823        | 3.0   | 554010 | 1.0758          | 21.7197 | 10.1392 | 21.1499 | 21.173    | 87.4589 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.0
- Datasets 2.8.0
- Tokenizers 0.13.2