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This model was trained on a Japanese dataset and built with Qwen.

Evaluation

llm-jp-eval script(colab)

!git clone https://github.com/llm-jp/llm-jp-eval.git
!cd llm-jp-eval && pip install -e .
!cd llm-jp-eval && python scripts/preprocess_dataset.py --dataset-name all --output-dir ./dataset_dir
!cd llm-jp-eval && python scripts/evaluate_llm.py -cn config.yaml model.pretrained_model_name_or_path=jaeyong2/Qwen2.5-0.5B-Instruct-JaMagpie-Preview tokenizer.pretrained_model_name_or_path=jaeyong2/Qwen2.5-0.5B-Instruct-JaMagpie-Preview dataset_dir=./dataset_dir/1.4.1/evaluation/test
llm-jp-eval Qwen2.5-3B-Instruct finetuning-model
AVG 0.4921 0.4895
CG 0.1000 0
EL 0.4770 0.4431
FA 0.1210 0.1246
HE 0.5550 0.5650
MC 0.7133 0.7900
MR 0.5400 0.6100
MT 0.6391 0.5982
NLI 0.6640 0.6640
QA 0.2638 0.3165
RC 0.8481 0.7837

License

Qwen/Qwen2.5-3B-Instruct : https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE

Acknowledgement

This research is supported by TPU Research Cloud program.

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