A benchmark code of hwtcm.
See the codeA Comprehensive Benchmark for Evaluating Large Language Models in Traditional Chinese Medicine.
The dataset is available at https://huggingface.co/datasets/Monor/hwtcm
| multiple-choice questions(单选题) | multiple-answers questions(多选题) | True/False questions(判断题) | |
|---|---|---|---|
| llama3:8b | 21.94% | 17.71% | 46.56% |
| phi3:14b-instruct | 26.93% | 1.04% | 38.93% |
| aya:8b | 17.85% | 1.04% | 34.35% |
| mistral:7b-instruct | 21.76% | 2.08% | 48.09% |
| qwen1.5-7b-chat | 51.35% | 13.54% | 46.56% |
| qwen1.5-14b-chat | 69.94% | 78.12% | 31.30% |
| huangdi-13b-chat | 21.73% | 45.83% | 0.00% |
| canggong-14b-chat(SFT) Ours | 55.98% | 4.17% | 23.66% |
| canggong-14b-chat(DPO) Ours | 72.33% | 2.08% | 45.80% |
canggong-14b-chat is an LLM of traditional Chinese medicine still in training.
4 commits
Python
100.0%
A benchmark code of hwtcm.
See the codeA Comprehensive Benchmark for Evaluating Large Language Models in Traditional Chinese Medicine.
The dataset is available at https://huggingface.co/datasets/Monor/hwtcm
| multiple-choice questions(单选题) | multiple-answers questions(多选题) | True/False questions(判断题) | |
|---|---|---|---|
| llama3:8b | 21.94% | 17.71% | 46.56% |
| phi3:14b-instruct | 26.93% | 1.04% | 38.93% |
| aya:8b | 17.85% | 1.04% | 34.35% |
| mistral:7b-instruct | 21.76% | 2.08% | 48.09% |
| qwen1.5-7b-chat | 51.35% | 13.54% | 46.56% |
| qwen1.5-14b-chat | 69.94% | 78.12% | 31.30% |
| huangdi-13b-chat | 21.73% | 45.83% | 0.00% |
| canggong-14b-chat(SFT) Ours | 55.98% | 4.17% | 23.66% |
| canggong-14b-chat(DPO) Ours | 72.33% | 2.08% | 45.80% |
canggong-14b-chat is an LLM of traditional Chinese medicine still in training.
4 commits
Python
100.0%