metadata

language:
  - ko
  - en
tags:
  - generated_from_trainer
datasets:
  - >-
    KETI-AIR/aihub_koenzh_food_translation,KETI-AIR/aihub_scitech_translation,KETI-AIR/aihub_scitech20_translation,KETI-AIR/aihub_socialtech20_translation,KETI-AIR/aihub_spoken_language_translation
metrics:
  - bleu
model-index:
  - name: ko2en_bidirection2
    results:
      - task:
          name: Translation
          type: translation
        dataset:
          name: >-
            KETI-AIR/aihub_koenzh_food_translation,KETI-AIR/aihub_scitech_translation,KETI-AIR/aihub_scitech20_translation,KETI-AIR/aihub_socialtech20_translation,KETI-AIR/aihub_spoken_language_translation
            koen,none,none,none,none
          type: >-
            KETI-AIR/aihub_koenzh_food_translation,KETI-AIR/aihub_scitech_translation,KETI-AIR/aihub_scitech20_translation,KETI-AIR/aihub_socialtech20_translation,KETI-AIR/aihub_spoken_language_translation
          args: koen,none,none,none,none
        metrics:
          - name: Bleu
            type: bleu
            value: 51.5949
license: apache-2.0
pipeline_tag: translation

ko2en_bidirection2

This model is a fine-tuned version of KETI-AIR/long-ke-t5-base on the KETI-AIR/aihub_koenzh_food_translation,KETI-AIR/aihub_scitech_translation,KETI-AIR/aihub_scitech20_translation,KETI-AIR/aihub_socialtech20_translation,KETI-AIR/aihub_spoken_language_translation koen,none,none,none,none dataset. It achieves the following results on the evaluation set:

Loss: 0.5716
Bleu: 51.5949
Gen Len: 28.8348

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: 16
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 128
total_eval_batch_size: 128
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	Bleu	Gen Len
0.7004	1.0	187524	0.6461	28.0622	17.8368
0.6176	2.0	375048	0.5967	29.3033	17.8281
0.5642	3.0	562572	0.5716	30.0045	17.8366

Framework versions

Transformers 4.25.1
Pytorch 1.12.0
Datasets 2.8.0
Tokenizers 0.13.2