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Update README.md

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@@ -28,8 +28,8 @@ Evaluation was run on a held-out validation set (50 examples):
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  | Metric | Before FT | After FT |
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  |------|-----------|----------|
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- | Tool Selection Accuracy | **92.0%** | **98.0%** |
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- | Absolute Gain | – | **+6.0%** |
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  This shows the model learns **better tool selection and call consistency**, even though the base model already performs strongly.
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  | Metric | Before FT | After FT |
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  |------|-----------|----------|
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+ | Tool Selection Accuracy | **88.0%** | **98.0%** |
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+ | Absolute Gain | – | **+10.0%** |
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  This shows the model learns **better tool selection and call consistency**, even though the base model already performs strongly.
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