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Upload RT-DETRv2 voucher classifier

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README.md CHANGED
@@ -59,18 +59,30 @@ This model is a fine-tuned version of [PekingU/rtdetr_v2_r101vd](https://hugging
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  ### Performance Metrics
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  **Final Evaluation Results:**
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- **Model Confidence:**
 
 
 
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- **Performance by Object Size:**
 
 
 
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- **Dataset Information:**
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- *Training Dataset:*
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- - **Digital invoices**: 147 samples (29.0%)
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- - **Fisico receipts**: 241 samples (47.5%)
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- - **Tesoreria receipts**: 119 samples (23.5%)
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- - **Total training samples**: 507
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- *Evaluation Dataset:*
 
 
 
 
 
 
 
 
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  - **Total evaluation samples**: 551
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  **Model Configuration:**
@@ -94,7 +106,7 @@ This model is a fine-tuned version of [PekingU/rtdetr_v2_r101vd](https://hugging
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  ### MLflow Tracking
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- - **MLflow Run ID**: ad012ef1dbbd4b61b39213442a1ca3a2
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  - **MLflow Experiment**: RT-DETRv2_Voucher_Classification
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  ### Performance Metrics
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  **Final Evaluation Results:**
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+ **Overall Detection Performance:**
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+ - **mAP**: 0.0000
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+ - **mAP@50**: 0.0000
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+ - **mAP@75**: 0.0000
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+ **Per-Class Average Precision:**
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+ - **Digital invoices**: 0.0000 (needs improvement)
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+ - **Fisico receipts**: 0.0000 (needs improvement)
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+ - **Tesoreria receipts**: 0.0000 (needs improvement)
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+ **Model Confidence:**
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+ - **Digital invoices mean confidence**: 0.7044 (moderate)
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+ - **Fisico receipts mean confidence**: 0.5937 (low)
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+ - **Tesoreria receipts mean confidence**: 0.5683 (low)
 
 
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+ **Performance by Object Size:**
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+ - **Small objects**: 0.0000
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+ - **Medium objects**: -1.0000
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+ - **Large objects**: 0.0000
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+
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+ **Evaluation Dataset:**
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+ - **Digital invoices**: 157 samples (28.5%)
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+ - **Fisico receipts**: 261 samples (47.4%)
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+ - **Tesoreria receipts**: 133 samples (24.1%)
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  - **Total evaluation samples**: 551
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  **Model Configuration:**
 
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  ### MLflow Tracking
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+ - **MLflow Run ID**: b7fca7191e0c4de6883f809c8d3f4e0c
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  - **MLflow Experiment**: RT-DETRv2_Voucher_Classification
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