kd4_opus-mt-ko-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-ko-en on the kde4 dataset. It achieves the following results on the evaluation set:
- Loss: 1.3924
- Bleu: 32.1162
Model description
More information needed
Intended uses & limitations
More information needed
Usage
You can use this model directly with a pipeline for translation language modeling:
>>> from transformers import pipeline
>>> translator = pipeline('translation',model='chunwoolee0/kd4_opus-mt-ko-e')
>>> translator("점심 식사 후에 산책가자.")
[{'translation_text': "Let's go for a walk after noon."}]
>>> translator("이 강좌는 허깅페이스가 만든 거야.")
[{'translation_text': 'This is a course by Huggingspace.'}]
>>> translator("오늘은 늦게 일어났다.")
[{'translation_text': "I'm up late today."}]
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: 3
Training results
Step Training Loss 500 1.858500 1000 1.781400 1500 1.715200 2000 1.678100 2500 1.546600 3000 1.488700 3500 1.503500 4000 1.455100 4500 1.419100 5000 1.393400 5500 1.357100 6000 1.339400 TrainOutput(global_step=6474, training_loss=1.532715692246148, metrics={'train_runtime': 1035.7775, 'train_samples_per_second': 199.957, 'train_steps_per_second': 6.25, 'total_flos': 2551308264603648.0, 'train_loss': 1.532715692246148, 'epoch': 3.0})
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3