README.md

metadata

base_model:
  - Qwen/Qwen2.5-0.5B-Instruct
datasets:
  - Augmentation-Scaling-Laws/math-seed-data
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
model-index:
  - name: ECE-Qwen0.5B-FT-V2
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 25.26
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/ECE-Qwen0.5B-FT-V2
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 7.63
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/ECE-Qwen0.5B-FT-V2
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 1.21
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/ECE-Qwen0.5B-FT-V2
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 2.24
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/ECE-Qwen0.5B-FT-V2
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 0.89
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/ECE-Qwen0.5B-FT-V2
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 7.4
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/ECE-Qwen0.5B-FT-V2
          name: Open LLM Leaderboard

Model Description

The model you’re using is based on Qwen/Qwen2.5-0.5B-Instruct, a powerful AI designed to follow instructions across a wide range of tasks. Through specialized fine-tuning, this model has been trained to become highly proficient in solving complex mathematical problems. By using a dataset specifically focused on math (Augmentation-Scaling-Laws/math-seed-data), it has gained the ability to handle advanced calculations and mathematical reasoning, making it an ideal assistant for anyone needing help with math-related tasks or challenges.

• Developed by: Youri Lalain (@Youlln)
• Organization: ECE engineering school

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	7.44
IFEval (0-Shot)	25.26
BBH (3-Shot)	7.63
MATH Lvl 5 (4-Shot)	1.21
GPQA (0-shot)	2.24
MuSR (0-shot)	0.89
MMLU-PRO (5-shot)	7.40