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.