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Mistral 7B Dolphin Sft by CorticalStack

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  4bit   Autotrain compatible   Endpoints compatible   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/CorticalStack/mistral-7b-dolphin-sft 

Mistral 7B Dolphin Sft Benchmarks

ARC: 57.25 vs 96.7 (so35)-40.8%
HellaSwag: 83.01 vs 95.3 (gpt4)-12.9%
MMLU: 62.59 vs 88.3 (so35)-29.1%
TruthfulQA: 48.91 vs 59 (gpt4)-17.1%
WinoGrande: 77.51 vs 87.5 (gpt4)-11.4%
GSM8K: 35.78 vs 96.4 (so35)-62.9%
LLME Score: 0.15701
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Dolphin Sft (CorticalStack/mistral-7b-dolphin-sft)
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Mistral 7B Dolphin Sft Parameters and Internals

Additional Notes 
Fine-tuning involved LoRA with parameters: r=256, alpha=128, dropout=0.0. Trained with adamw_torch_fused optimizer, batch size of 4, gradient accumulation steps of 6, for 100 max steps, and learning rate of 0.0002.
Training Details 
Data Sources:
cognitivecomputations/dolphin
Methodology:
SFT fine-tuning
Context Length:
2048
LLM NameMistral 7B Dolphin Sft
Repository 🤗https://huggingface.co/CorticalStack/mistral-7b-dolphin-sft 
Model Size7b
Required VRAM14.4 GB
Updated2025-08-15
MaintainerCorticalStack
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than CorticalStack/mistral-7b-dolphin-sft.

Rank the Mistral 7B Dolphin Sft Capabilities

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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