README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - qwen2
  - trl
base_model: unsloth/qwen2.5-14b-bnb-4bit
model-index:
  - name: Qwen2.5-Math-14B-Instruct-Alpha
    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: 59.81
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=qingy2019/Qwen2.5-Math-14B-Instruct-Alpha
          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: 47.75
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=qingy2019/Qwen2.5-Math-14B-Instruct-Alpha
          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: 23.11
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=qingy2019/Qwen2.5-Math-14B-Instruct-Alpha
          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: 16
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=qingy2019/Qwen2.5-Math-14B-Instruct-Alpha
          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: 17.95
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=qingy2019/Qwen2.5-Math-14B-Instruct-Alpha
          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: 48.12
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=qingy2019/Qwen2.5-Math-14B-Instruct-Alpha
          name: Open LLM Leaderboard

Uploaded model

• Developed by: qingy2019
• License: apache-2.0
• Finetuned from model : unsloth/qwen2.5-14b-bnb-4bit

Huge thanks to Unsloth and the Huggingface TRL library.

This model is Qwen 2.5 14B fine tuned for a full epoch on the high quality garage-bAInd/Open-Platypus dataset for STEM reasoning.

Training Detail	Value
Epochs	1
Steps	2077
Loss	0.4218
Batch size	4
Gradient Acc. Steps	3
Learning Rate	2e-4
LR Scheduler	cosine
Rank	32
Rank-Stabilized LoRA	Yes
Warm up steps	5
Weight Decay	0.01
Seed	3407

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	35.46
IFEval (0-Shot)	59.81
BBH (3-Shot)	47.75
MATH Lvl 5 (4-Shot)	23.11
GPQA (0-shot)	16.00
MuSR (0-shot)	17.95
MMLU-PRO (5-shot)	48.12