SauerkrautLM-v2-14b-DPO

Maintained By
VAGOsolutions

SauerkrautLM-v2-14b-DPO

PropertyValue
Parameter Count14.8B
LicenseApache 2.0
Supported LanguagesEnglish, German, Italian, French, Portuguese, Dutch, Arabic, Spanish
Model TypeDPO Fine-tuned
Base ModelSauerkrautLM-v2-14b-SFT

What is SauerkrautLM-v2-14b-DPO?

SauerkrautLM-v2-14b-DPO is an advanced language model that builds upon its SFT predecessor through Direct Preference Optimization (DPO). This model implements a unique three-phase training approach, combining traditional SFT with DPO techniques to enhance both English performance and German language capabilities.

Implementation Details

The model utilizes a sophisticated training procedure involving three distinct phases: two SFT phases targeting 25% and 20% of layers respectively with 0.6B tokens each, followed by a DPO phase targeting 15% of layers with 80M tokens. The model achieves impressive benchmark scores, including 74.12% on IFEval and 50.93% on BBH (3-Shot).

  • Spectrum Fine-Tuning with targeted layer approach
  • Enhanced function calling with improved German irrelevance handling
  • Balanced dataset composition for maintaining multilingual capabilities
  • BF16 tensor type for optimal performance

Core Capabilities

  • Multilingual support across 8 languages
  • Enhanced English language performance while maintaining German proficiency
  • Optimized function calling specifically for German language contexts
  • Strong performance on various benchmarks including MMLU-PRO (45.75% accuracy)

Frequently Asked Questions

Q: What makes this model unique?

The model's distinctive three-phase training approach and specific optimization for German-English language handling, combined with its specialized function calling capabilities, sets it apart from traditional language models.

Q: What are the recommended use cases?

The model is particularly well-suited for multilingual applications, especially those requiring strong English-German capabilities, function calling, and general language understanding tasks across multiple domains.

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