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Gemma 2 9B It SPPO Iter3 by UCLA-AGI

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  9087   
  Arxiv:2405.00675   Autotrain compatible   Conversational   Dataset:openbmb/ultrafeedback   En   Endpoints compatible   Gemma2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3 

Gemma 2 9B It SPPO Iter3 Benchmarks

MMLU Pro: 31.4
GPQA: 11.86
MUSR: 11.34
BBH: 42.54
IFEval: 31.67 vs 88 (so35)-64%
LLME Score: 0.35701
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2 9B It SPPO Iter3 (UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3)

Gemma 2 9B It SPPO Iter3 Parameters and Internals

Model Type 
GPT-like, text generation
Supported Languages 
en (NLP)
Training Details 
Data Sources:
openbmb/UltraFeedback, snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
Methodology:
Self-Play Preference Optimization, finetuning on synthetic datasets
Model Architecture:
GPT-like
LLM NameGemma 2 9B It SPPO Iter3
Repository 🤗https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3 
Model Size9b
Required VRAM18.6 GB
Updated2024-12-26
MaintainerUCLA-AGI
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
Supported Languagesen
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.43.0.dev0
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 UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3.

Rank the Gemma 2 9B It SPPO Iter3 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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Release v20241217
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