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
    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: 58.7008
license: apache-2.0
pipeline_tag: translation

ko2en

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: 0.5186
Bleu: 58.7008
Gen Len: 27.0073

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
0.6234	1.0	93762	0.5843	33.9843	17.5378
0.5334	2.0	187524	0.5369	35.3271	17.5388
0.4704	3.0	281286	0.5186	36.0533	17.5335

Framework versions

Transformers 4.25.1
Pytorch 1.12.0
Datasets 2.8.0
Tokenizers 0.13.2