NikshepShetty
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README.md
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type: other
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metrics:
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- type: meteor
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value: 0.
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- type: bleu
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value: 0.
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- type: cider
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value: 0.
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- type: capture
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value: 0.
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- type: rouge-l
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value: 0.
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---
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# Florence-2 DOCCI-FT LoRA Adapter
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## Evaluation results
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Our LoRA adapter shows
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| Metric | Base Model | Adapted Model | Improvement |
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|---------|------------|---------------|-------------|
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| METEOR | 0.
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| BLEU | 0.
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| CIDEr | 0.
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| CAPTURE | 0.
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| ROUGE-L | 0.
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type: other
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metrics:
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- type: meteor
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value: 0.267
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- type: bleu
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value: 0.185
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- type: cider
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value: 0.086
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- type: capture
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value: 0.576
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- type: rouge-l
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value: 0.287
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---
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# Florence-2 DOCCI-FT LoRA Adapter
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## Evaluation results
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Our LoRA adapter shows improvements over the base Florence-2 model across all metrics for MORE_DETAILED_CAPTION tag for 1000 images on the foundation-multimodal-models/DetailCaps-4870 dataset:
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| Metric | Base Model | Adapted Model | Improvement |
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|---------|------------|---------------|-------------|
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| METEOR | 0.213 | 0.267 | +25.4% |
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| BLEU | 0.110 | 0.185 | +68.2% |
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| CIDEr | 0.031 | 0.086 | +177.4% |
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| CAPTURE | 0.546 | 0.576 | +5.5% |
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| ROUGE-L | 0.275 | 0.287 | +4.4% |
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These results demonstrate that our LoRA adapter enhances the image captioning capabilities of the Florence-2 base model, particularly in generating more detailed and accurate captions.
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