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# sungju_finetuned-ko-to-en_ver3

This model is a fine-tuned version of [KETI-AIR-Downstream/long-ke-t5-base-translation-aihub-ko2en](https://huggingface.co/KETI-AIR-Downstream/long-ke-t5-base-translation-aihub-ko2en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0946
- Bleu: 28.4700

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "sungju_finetuned-ko-to-en_ver3", "results": []}]}
transformers pytorch tensorboard longt5 text2text-generation translation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #longt5 #text2text-generation #translation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# sungju_finetuned-ko-to-en_ver3

This model is a fine-tuned version of KETI-AIR-Downstream/long-ke-t5-base-translation-aihub-ko2en on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0946
- Bleu: 28.4700

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# sungju_finetuned-ko-to-en_ver3

This model is a fine-tuned version of KETI-AIR-Downstream/long-ke-t5-base-translation-aihub-ko2en on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0946
- Bleu: 28.4700 ## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #longt5 #text2text-generation #translation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # sungju_finetuned-ko-to-en_ver3

This model is a fine-tuned version of KETI-AIR-Downstream/long-ke-t5-base-translation-aihub-ko2en on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0946
- Bleu: 28.4700 ## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3