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Matter 0.2 7B DPO by 0-hero

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  Autotrain compatible   Conversational Dataset:0-hero/matter-0.2-alph...   En   Endpoints compatible   Mistral   Model-index   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/0-hero/Matter-0.2-7B-DPO 

Matter 0.2 7B DPO Benchmarks

MMLU Pro: 1.82
GPQA: 1.23
MUSR: 5.87
BBH: 10.06
IFEval: 33.03 vs 88 (so35)-62.5%
ARC: 63.31 vs 96.7 (so35)-34.5%
HellaSwag: 83.16 vs 95.3 (gpt4)-12.7%
MMLU: 62.9 vs 88.3 (so35)-28.8%
TruthfulQA: 50.3 vs 59 (gpt4)-14.7%
WinoGrande: 80.27 vs 87.5 (gpt4)-8.3%
GSM8K: 56.94 vs 96.4 (so35)-40.9%
MATH Lvl 5: 1.44
LLME Score: 0.21823
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Matter 0.2 7B DPO (0-hero/Matter-0.2-7B-DPO)

Matter 0.2 7B DPO Parameters and Internals

Model Type 
text-generation
Training Details 
Data Sources:
Matter-0.2-alpha
Data Volume:
>6B tokens
Input Output 
Input Format:
ChatML prompt format
LLM NameMatter 0.2 7B DPO
Repository 🤗https://huggingface.co/0-hero/Matter-0.2-7B-DPO 
Model Size7b
Required VRAM14.5 GB
Updated2025-02-22
Maintainer0-hero
Model Typemistral
Model Files  14.5 GB   14.5 GB
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32006
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than 0-hero/Matter-0.2-7B-DPO.

Rank the Matter 0.2 7B DPO 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 v20241227
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