metadata

base_model:
  - Qwen/Qwen2.5-Coder-14B-Instruct
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - qwen2
  - trl
  - chain-of-thought
  - reasoning
license: apache-2.0
language:
  - en
datasets:
  - PJMixers/Math-Multiturn-100K-ShareGPT
new_version: Daemontatox/CogitoZ14
library_name: transformers
model-index:
  - name: CogitoZ14
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: wis-k/instruction-following-eval
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 66.37
            name: averaged accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FCogitoZ14
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: SaylorTwift/bbh
          split: test
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 46.48
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FCogitoZ14
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: lighteval/MATH-Hard
          split: test
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 20.77
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FCogitoZ14
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 8.84
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FCogitoZ14
          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: 9.07
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FCogitoZ14
          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: 33.33
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FCogitoZ14
          name: Open LLM Leaderboard

Uploaded Model

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

Overview

This Qwen2 model has been finetuned using Unsloth and Hugging Face's TRL (Transformers Reinforcement Learning) library. The finetuning process achieved a 2x speedup compared to traditional methods.

Features

Optimized for text generation and inference tasks.
Lightweight with 4-bit quantization for efficient performance.
Compatible with various NLP and code-generation applications.

Acknowledgments

This model leverages Unsloth’s advanced optimization techniques to ensure faster training and inference.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here! Summarized results can be found here!

Metric	Value (%)
Average	30.81
IFEval (0-Shot)	66.37
BBH (3-Shot)	46.48
MATH Lvl 5 (4-Shot)	20.77
GPQA (0-shot)	8.84
MuSR (0-shot)	9.07
MMLU-PRO (5-shot)	33.33