Update README.md

README.md

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 ---
 library_name: sklearn
+tags:
+- regression
+- scikit-learn
+- UCS
+- cement
+license: mit
 ---
+
+# Model Card: RandomForestRegressor for UCS Prediction
+
+## Model Overview
+
+This model is a `RandomForestRegressor` trained to predict the Unconfined Compressive Strength (UCS) of soil-cement mixtures based on the following features:
+
+- **Curing Period (`curing_period`)**: Duration in days.
+- **Compaction Rate (`compaction_rate`)**: Numerical value.
+- **Cement Percentage (`cement_percent`)**: Percentage of cement in the mixture.
+
+## Performance
+
+The model achieved an R² score of **0.968** during cross-validation, indicating a high level of accuracy in predicting UCS values.
+
+## Feature Ranges
+
+- **Curing Period**: Min = 0.0 days, Max = 28.0 days, Mean = 11.06 days
+- **Compaction Rate**: Min = 0.5, Max = 1.25, Mean = 0.989
+- **Cement Percentage**: Min = 0.0%, Max = 10.0%, Mean = 5.77%
+
+## Usage
+
+To utilize this model, load the `model.joblib` file and input data within the specified feature ranges to obtain UCS predictions.
+
+## Limitations
+
+The model is calibrated for predictions within the specified feature ranges. Using it outside these ranges may result in less accurate predictions. It is specifically designed for soil-cement mixtures and may not be applicable to other materials.
+
+## Author
+
+[Your Name or Team Name]
+
+## Contact
+
+For inquiries or suggestions, please contact [your email address].