edgan8
commented
5 months ago My understanding is the evalplus MBPP has been sanitized so that the prompts / answers are substantially different from the original: https://github.com/evalplus/evalplus/releases/tag/v0.2.0 . The MBPPPlus task here might be closer to what's in evalplus.
Hi, I was checking the greedy decoding pass@1 score for Llama3-8B base model and Llama3-8B-Instruct model against https://evalplus.github.io/leaderboard.html I found that in the diagram, Llama3-8B-Instruct gets 59.5 pass@1 accuracy for greedy decoding, while Llama3-8B pass@1 accuracy is 51.6. The task is MBPP. However, when I use this code base, I get 51.6 for Llama3-8B-Instruct and 45.4 for Llama3-8B base. I set the max_generation_length to 2048 when evaluating for MBPP. Strangely, I was managed to reproduce the greedy decoding pass@1 score for HumanEval. Do you know what can go wrong with the evaluation? Here is the full result
{
"mbpp": {
"pass@1": 0.454
},
"config": {
"prefix": "",
"do_sample": false,
"temperature": 0.2,
"top_k": 0,
"top_p": 0.95,
"n_samples": 1,
"eos": "<|endoftext|>",
"seed": 0,
"model": "meta-llama/Meta-Llama-3-8B",
"modeltype": "causal",
"peft_model": null,
"revision": null,
"use_auth_token": false,
"trust_remote_code": false,
"tasks": "mbpp",
"instruction_tokens": null,
"batch_size": 1,
"max_length_generation": 2048,
"precision": "fp32",
"load_in_8bit": false,
"load_in_4bit": false,
"left_padding": false,
"limit": null,
"limit_start": 0,
"save_every_k_tasks": -1,
"postprocess": true,
"allow_code_execution": true,
"generation_only": false,
"load_generations_path": null,
"load_data_path": null,
"metric_output_path": "evaluation_results.json",
"save_generations": false,
"load_generations_intermediate_paths": null,
"save_generations_path": "generations.json",
"save_references": false,
"save_references_path": "references.json",
"prompt": "prompt",
"max_memory_per_gpu": null,
"check_references": false, } }
{
"mbpp": {
"pass@1": 0.516
},
"config": {
"prefix": "",
"do_sample": false,
"temperature": 0.2,
"top_k": 0,
"top_p": 0.95,
"n_samples": 1,
"eos": "<|endoftext|>",
"seed": 0,
"model": "meta-llama/Meta-Llama-3-8B-Instruct",
"modeltype": "causal",
"peft_model": null,
"revision": null,
"use_auth_token": false,
"trust_remote_code": false,
"tasks": "mbpp",
"instruction_tokens": null,
"batch_size": 1,
"max_length_generation": 2048,
"precision": "fp32",
"load_in_8bit": false,
"load_in_4bit": false,
"left_padding": false,
"limit": null,
"limit_start": 0,
"save_every_k_tasks": -1,
"postprocess": true,
"allow_code_execution": true,
"generation_only": false,
"load_generations_path": null,
"load_data_path": null,
"metric_output_path": "evaluation_results.json",
"save_generations": false,
"load_generations_intermediate_paths": null,
"save_generations_path": "generations.json",
"save_references": false,
"save_references_path": "references.json",
"prompt": "prompt",
"max_memory_per_gpu": null,
"check_references": false, } } Thank you for your attention