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README.md
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- lora
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datasets:
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- Multimodal-Fatima/FGVC_Aircraft_train
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- lora
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datasets:
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- Multimodal-Fatima/FGVC_Aircraft_train
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---
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# pixtral_aerial_VQA_adapter
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## Model Details
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- **Type**: LoRA Adapter
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- **Total Parameters**: 6,225,920
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- **Memory Usage**: 23.75 MB
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- **Precisions**: torch.float32
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- **Layer Types**:
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- lora_A: 40
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- lora_B: 40
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## Intended Use
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- **Primary intended uses**: Processing aerial footage of construction sites for structural and construction surveying.
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- Can also be applied to any detailed VQA use cases with aerial footage.
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## Training Data
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- **Dataset**:
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1. FloodNet Track 2 dataset
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2. Subset of FGVC Aircraft dataset
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3. Custom dataset of 10 image-caption pairs created using Pixtral
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## Training Procedure
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- **Training method**: LoRA (Low-Rank Adaptation)
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- **Base model**: Ertugrul/Pixtral-12B-Captioner-Relaxed
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- **Training hardware**: Nebius-hosted NVIDIA H100 machine
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