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Gemma2 Gutenberg 9B by nbeerbower

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  Autotrain compatible Base model:finetune:ucla-agi/g... Base model:ucla-agi/gemma-2-9b...   Conversational Dataset:jondurbin/gutenberg-dp...   Endpoints compatible   Gemma2   Model-index   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nbeerbower/gemma2-gutenberg-9B 

Gemma2 Gutenberg 9B Benchmarks

MMLU Pro: 35.47
GPQA: 11.74
MUSR: 16.71
BBH: 42.36
IFEval: 27.96 vs 88 (so35)-68.2%
MATH Lvl 5: 1.66
LLME Score: 0.28246
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma2 Gutenberg 9B (nbeerbower/gemma2-gutenberg-9B)

Gemma2 Gutenberg 9B Parameters and Internals

Model Type 
text-generation
Additional Notes 
Average performance across benchmarks is 22.61.
Training Details 
Data Sources:
jondurbin/gutenberg-dpo-v0.1
Methodology:
Finetuned using an RTX 4090 using ORPO for 3 epochs.
Hardware Used:
RTX 4090
LLM NameGemma2 Gutenberg 9B
Repository 🤗https://huggingface.co/nbeerbower/gemma2-gutenberg-9B 
Base Model(s)  Gemma 2 9B It SPPO Iter3   UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
Model Size9b
Required VRAM18.6 GB
Updated2024-12-26
Maintainernbeerbower
Model Typegemma2
Model Files  4.9 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.7 GB: 4-of-4
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.42.4
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than nbeerbower/gemma2-gutenberg-9B.

Rank the Gemma2 Gutenberg 9B 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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