Adapters MCQA SFT by berquetR

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  Arxiv:1910.09700   Adapter Base model:adapter:tonymdsa/ph... Base model:tonymdsa/phi-2 fine...   Finetuned   Lora   Peft   Region:us   Safetensors

Adapters MCQA SFT Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Adapters MCQA SFT (berquetR/adapters_MCQA_SFT)

Adapters MCQA SFT Parameters and Internals

LLM NameAdapters MCQA SFT
Repository ๐Ÿค—https://huggingface.co/berquetR/adapters_MCQA_SFT 
Base Model(s)  TonyMDSA/Phi-2_finetune_MCQ   TonyMDSA/Phi-2_finetune_MCQ
Required VRAM0 GB
Updated2024-08-15
MaintainerberquetR
Model Files  0.3 GB   0.0 GB   0.0 GB   0.0 GB
Model ArchitectureAdapter
Model Max Length2048
Is Biasednone
Tokenizer ClassCodeGenTokenizer
Padding Token<|endoftext|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesup_proj|q_proj|lm_head|v_proj|down_proj|o_proj|gate_proj|k_proj
LoRA Alpha8
LoRA Dropout0.05
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than berquetR/adapters_MCQA_SFT.

Rank the Adapters MCQA SFT Capabilities

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