Phi 3 Mini 4K Instruct DPO EPFL by StefanKrsteski

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  Adapter Base model:adapter:microsoft/p... Base model:microsoft/phi-3-min... Dataset:argilla/ultrafeedback-... Dataset:flax-sentence-embeddin...   En   Finetuned   Instruct   Lora   Peft   Region:us   Safetensors

Phi 3 Mini 4K Instruct DPO EPFL Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi 3 Mini 4K Instruct DPO EPFL (StefanKrsteski/Phi-3-mini-4k-instruct-DPO-EPFL)

Phi 3 Mini 4K Instruct DPO EPFL Parameters and Internals

Model Type 
Language Model, Fine-tuned with direct preference optimization (DPO)
Use Cases 
Applications:
AI-Tutor system
Supported Languages 
en (English)
Training Details 
Data Sources:
argilla/ultrafeedback-binarized-preferences-cleaned, flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl
Methodology:
Trained on the EPFL SCITAS cluster using a 32GB GPU
Hardware Used:
32GB GPU
LLM NamePhi 3 Mini 4K Instruct DPO EPFL
Repository ๐Ÿค—https://huggingface.co/StefanKrsteski/Phi-3-mini-4k-instruct-DPO-EPFL 
Base Model(s)  Phi 3 Mini 4K Instruct   microsoft/Phi-3-mini-4k-instruct
Required VRAM0 GB
Updated2025-02-22
MaintainerStefanKrsteski
Instruction-BasedYes
Model Files  0.1 GB   0.1 GB   0.0 GB   0.0 GB
Supported Languagesen
Model ArchitectureAdapter
Model Max Length4096
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesk_proj|up_proj|v_proj|gate_proj|o_proj|q_proj|down_proj
LoRA Alpha16
LoRA Dropout0.1
R Param32

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Note: green Score (e.g. "73.2") means that the model is better than StefanKrsteski/Phi-3-mini-4k-instruct-DPO-EPFL.

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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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227