Update README.md

README.md

@@ -27,7 +27,7 @@ The task is to predict whether a book is **recommended to everyone** based on ta
 ## Model Details
 
 - **Developed by:** Bareethul Kader
-- **Framework:** AutoGluon (v1.1)  
+- **Framework:** AutoGluon
 - **Repository:** [bareethul/AutoML-books-classification](https://huggingface.co/bareethul/AutoML-books-classification)  
 - **License:** CC BY 4.0  
 
@@ -64,7 +64,7 @@ The task is to predict whether a book is **recommended to everyone** based on ta
 
 - **AutoML framework:** AutoGluon TabularPredictor  
 - **Evaluation metric:** Accuracy  
-- **Budget:** ~1 minute training time, small scale search  
+- **Budget:** 300 seconds training time, small scale search  
 - **Hardware:** Google Colab (T4 GPU not required, CPU sufficient)  
 - **Search Space:**  
   - Tree based models: LightGBM, XGBoost, ExtraTrees, RandomForest  
@@ -79,13 +79,13 @@ The task is to predict whether a book is **recommended to everyone** based on ta
 
 | Rank | Model                     | Test Accuracy | Validation Accuracy |
 |------|---------------------------|---------------|----------------------|
-| 1    | RandomForestEntr_BAG_L1   | **0.55**      | ~0.65               |
-| 2    | LightGBM_r96_BAG_L2       | 0.53          | ~0.72               |
-| 3    | LightGBMLarge_BAG_L2      | 0.53          | ~0.74               |
+| 1    | RandomForestEntr_BAG_L1   | **0.55**      | 0.65               |
+| 2    | LightGBM_r96_BAG_L2       | 0.53          | 0.72               |
+| 3    | LightGBMLarge_BAG_L2      | 0.53          | 0.74               |
 
 - **Best model (AutoGluon selected):** `RandomForestEntr_BAG_L1`  
 - **Test Accuracy:** ~0.55  
-- **Validation Accuracy (best across runs):** up to ~0.75 (LightGBM variants)  
+- **Validation Accuracy (best across runs):** up to 0.75 (LightGBM variants)  
 
 Note: The **“best model”** may vary depending on random splits and seeds.  
 While AutoGluon reported `RandomForestEntr_BAG_L1` as best in this run, LightGBM models sometimes achieved higher validation accuracy but generalized less strongly.