Calcium-Opus-14B-Merge

Calcium-Opus-14B-Merge is based on the Qwen 2.5 14B modality architecture, designed to enhance the reasoning capabilities of 14B-parameter models. These models have proven effective in context understanding, reasoning, and mathematical problem-solving. It has been fine-tuned using a long chain-of-thought reasoning model and specialized datasets, with a focus on chain-of-thought (CoT) reasoning for problem-solving. This model is optimized for tasks requiring logical reasoning, detailed explanations, and multi-step problem-solving, making it ideal for applications such as instruction-following, text generation, and complex reasoning tasks.

This is a merge of pre-trained language models created using mergekit.

Merge Method

This model was merged using the Model Stock merge method using Qwen/Qwen2.5-14B-Instruct as a base.

Models Merged

The following models were included in the merge:

• prithivMLmods/Calcium-Opus-14B-Elite
• prithivMLmods/QwQ-LCoT-14B-Conversational

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: prithivMLmods/Calcium-Opus-14B-Elite
  - model: prithivMLmods/QwQ-LCoT-14B-Conversational
merge_method: model_stock
base_model: Qwen/Qwen2.5-14B-Instruct
parameters:
  normalize: false
  int8_mask: true
dtype: bfloat16
tokenizer_source: "Qwen/Qwen2.5-14B-Instruct"

Open LLM Leaderboard Evaluation Results

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

Metric	Value (%)
Average	35.80
IFEval (0-Shot)	49.49
BBH (3-Shot)	46.77
MATH Lvl 5 (4-Shot)	33.08
GPQA (0-shot)	16.11
MuSR (0-shot)	20.93
MMLU-PRO (5-shot)	48.40