CPsyExam

CPsyExam: A Chinese Benchmark for Evaluating Psychology using Examinations

Leaderboard

The following tables display the performance of models in the CPsyExam-KG and CPsyExam-CA

CPsyExam-KG

Model	MCQA(Zero-shot)	MRQA(Zero-shot)	MCQA(Five-shot)	MRQA(Five-shot)	Average(Zero-shot)	Average(Five-shot)
Open-sourced Models
ChatGLM2-6B	49.89	9.86	53.81	14.85	39.81	44.00
ChatGLM3-6B	53.51	5.63	55.75	5.51	41.46	43.10
YI-6B	33.26	0.26	25.39	14.01	24.95	22.31
QWEN-14B	24.99	1.54	38.17	13.19	19.08	31.88
YI-34B	25.03	1.15	33.69	18.18	24.95	22.31
Psychology-oriented Models
MeChat-6B	50.24	4.10	51.79	11.91	38.62	41.75
MindChat-7B	49.25	6.27	56.92	5.51	38.43	43.97
MindChat-8B	26.50	0.00	26.50	0.13	19.83	19.86
Ours-SFT-6B	52.95	10.50	58.77	2.94	42.26	44.71
Api-based Models
ERNIE-Bot	52.48	6.66	56.10	10.37	40.94	44.58
ChatGPT	57.43	11.14	61.53	24.71	45.78	52.26
ChatGLM	63.29	26.12	73.85	42.13	53.93	65.86
GPT4	76.56	10.76	78.63	43.79	59.99	69.85

CPsyExam-CA

Model	MCQA(Zero-shot)	MRQA(Zero-shot)	MCQA(Five-shot)	MRQA(Five-shot)	Average(Zero-shot)	Average(Five-shot)
Open-sourced Models
ChatGLM2-6B	52.50	16.00	48.50	20.00	43.38	41.38
ChatGLM3-6B	47.00	17.00	47.33	13.50	39.50	38.88
YI-6B	38.83	0.00	20.00	13.25	29.12	18.63
QWEN-14B	20.33	2.00	30.00	14.00	15.75	26.00
YI-34B	20.50	0.50	22.33	8.00	15.50	19.39
Psychology-oriented Models
MeChat-6B	48.67	13.50	44.83	10.50	39.86	36.25
MindChat-7B	40.83	5.00	33.83	4.50	31.88	26.50
MindChat-8B	34.17	0.00	34.17	0.00	25.63	25.63
Ours-SFT-6B	46.50	5.50	48.67	13.00
Api-based Models
ERNIE-Bot	42.50	8.50	50.67	12.00	34.00	41.00
ChatGPT	47.33	9.00	52.67	29.50	37.75	46.88
ChatGLM	69.00	20.50	65.33	42.50	56.88	59.63
GPT4	60.33	13.00	64.17	39.50	48.50	58.00

Evaluation

Usage

run_example.sh MODEL MODEL_NAME_OR_PATH/API_URL TASK SPLIT GPUS N_SHOT

Parameters

• MODEL:The identifier for the model used for evaluation. This can be a local model name or an identifier for online evaluation.

• MODEL_NAME_OR_PATH:The path to the model file or directory for local evaluation, or the base URL for the API when performing online evaluations.

• TASK:The name of the task for which the evaluation is being performed.

• SPLIT:The dataset split to use for evaluation, e.g., train, validation, test.

• GPUS:The GPU device ID(s) to use for the evaluation. Set to -1 if no GPU is used.

• N_SHOT:The number of shots to use for few-shot learning evaluations. Set this to 0 to disable few-shot learning.

Local Evaluation Example

bash evaluations/run_example.sh ChatGLM2 /data/pretrained_models/THUDM/chatglm2-6b ceval validation 0 0

Online Evaluation Example

bash evaluations/run_example.sh ERNIE-Bot-turbo https://your-openai-proxy.com ceval validation 0 0

LeaderBoard

If you are interesting in add your score to our leaderboard, please send your test answer to my email[email protected], Thank you.

SFT

SFT Data Preparation

PYTHONPATH=../related_repos/LLaMA-Factory/src:../src python cpsyexam_to_sft.py --task cpsyexam --task_dir <llmeval_path> --split train  --save_dir ../data --qa_file <qa_train_path>/cpsyexam_qa.json