README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - qwen2
  - trl
  - sft
base_model: unsloth/qwen2.5-0.5b-instruct-bnb-4bit
datasets:
  - UncovAI/fineweb_CC-MAIN-2024-18_100k_output_UncovAI_83362
model-index:
  - name: 83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
    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: 28.69
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=FlofloB/83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
          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: 8.13
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=FlofloB/83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
          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: 0
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=FlofloB/83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
          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: 3.13
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=FlofloB/83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
          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: 1.42
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=FlofloB/83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
          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: 6.17
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=FlofloB/83k_continued_pretraining_Qwen2.5-0.5B-Instruct_Unsloth_merged_16bit
          name: Open LLM Leaderboard

Uploaded model

• Developed by: FlofloB
• License: apache-2.0
• Finetuned from model : unsloth/qwen2.5-0.5b-instruct-bnb-4bit

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	7.92
IFEval (0-Shot)	28.69
BBH (3-Shot)	8.13
MATH Lvl 5 (4-Shot)	0.00
GPQA (0-shot)	3.13
MuSR (0-shot)	1.42
MMLU-PRO (5-shot)	6.17