---
license: apache-2.0
base_model: KETI-AIR/ke-t5-base
tags:
- generated_from_trainer
model-index:
- name: ke_t5_base_bongsoo_ko_en
  results: []
---

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# ke_t5_base_bongsoo_ko_en

This model is a fine-tuned version of [KETI-AIR/ke-t5-base](https://huggingface.co./KETI-AIR/ke-t5-base) 
on a [bongsoo/news_news_talk_en_ko](https://huggingface.co./datasets/bongsoo/news_talk_ko_en) dataset.

## Model description

KE-T5 is a pretrained-model of t5 text-to-text transfer transformers 
using the Korean and English corpus developed by KETI (한국전자연구원).
The vocabulary used by KE-T5 consists of 64,000 sub-word tokens 
and was created using Google's sentencepiece. 
The Sentencepiece model was trained to cover 99.95% of a 30GB corpus 
with an approximate 7:3 mix of Korean and English.

## Intended uses & limitations

Translation from Korean to English

## Usage

You can use this model directly with a pipeline for translation language modeling:

```python
>>> from transformers import pipeline
>>> translator = pipeline('translation', model='chunwoolee0/ke_t5_base_bongsoo_en_ko')

>>> translator("Let us go for a walk after lunch.")
[{'translation_text': '점심을 마치고 산책을 하러 가자.'}]


## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 5625 | 1.6845          | 12.2087 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3