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Math Gpt2 Sft by Sharathhebbar24

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Model Card on HF 🤗: https://huggingface.co/Sharathhebbar24/math_gpt2_sft 

Math Gpt2 Sft Benchmarks

ARC: 22.87 vs 96.7 (so35)-76.3%
HellaSwag: 30.41 vs 95.3 (gpt4)-68.1%
MMLU: 25.06 vs 88.3 (so35)-71.6%
TruthfulQA: 37.62 vs 59 (gpt4)-36.2%
WinoGrande: 51.54 vs 87.5 (gpt4)-41.1%
GSM8K: 0.68 vs 96.4 (so35)-99.3%
LLME Score: 0.23424
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Math Gpt2 Sft (Sharathhebbar24/math_gpt2_sft)

Math Gpt2 Sft Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model is a finetuned version of `Sharathhebbar24/math_gpt2` using `meta-math/MetaMathQA`.
Supported Languages 
languages (en), proficiency (unknown)
LLM NameMath Gpt2 Sft
Repository 🤗https://huggingface.co/Sharathhebbar24/math_gpt2_sft 
Model Size124.4m
Required VRAM0.5 GB
Updated2024-12-21
MaintainerSharathhebbar24
Model Typegpt2
Instruction-BasedYes
Model Files  0.5 GB
Supported Languagesen
Model ArchitectureGPT2LMHeadModel
Licenseapache-2.0
Model Max Length1024
Transformers Version4.39.3
Tokenizer ClassGPT2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than Sharathhebbar24/math_gpt2_sft.

Rank the Math Gpt2 Sft Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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