RichardErkhov/fblgit_-_UNA-POLAR-10.7B-InstructMath-v2-4bits

Quantization made by Richard Erkhov.

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UNA-POLAR-10.7B-InstructMath-v2 - bnb 4bits

• Model creator: https://huggingface.co/fblgit/
• Original model: https://huggingface.co/fblgit/UNA-POLAR-10.7B-InstructMath-v2/

Original model description:

language: - en license: cc-by-nc-nd-4.0 tags: - UNA - SOLAR - MathPILE datasets: - GAIR/MathPile model-index: - name: UNA-POLAR-10.7B-InstructMath-v2 results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 70.73 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-POLAR-10.7B-InstructMath-v2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 88.2 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-POLAR-10.7B-InstructMath-v2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 66.03 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-POLAR-10.7B-InstructMath-v2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 71.73 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-POLAR-10.7B-InstructMath-v2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 82.95 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-POLAR-10.7B-InstructMath-v2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 64.75 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/UNA-POLAR-10.7B-InstructMath-v2 name: Open LLM Leaderboard

UNA-POLAR-10.7B-InstructMath-v2

Model description

Its a UNA version with DPO over MathPILE Books out of the UNA-SOLAR-10.7B-Instruct-1.0

I used MathPILE OUTSTANDING Dataset of great Mathematic material in order to produce this beautiful model :)

Intended uses & limitations

If your model has inside UNA technology, cite.

Training and evaluation data

UNA-DPO over Attention and MLP's

Framework versions

• PEFT 0.7.1
• Transformers 4.36.2-UNA
• Pytorch 2.1.2+cu121
• Datasets 2.16.0
• Tokenizers 0.15.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	74.07
AI2 Reasoning Challenge (25-Shot)	70.73
HellaSwag (10-Shot)	88.20
MMLU (5-Shot)	66.03
TruthfulQA (0-shot)	71.73
Winogrande (5-shot)	82.95
GSM8k (5-shot)	64.75