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training_report.md

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 # Training Report - Ensemble
 
-    Generated: 2025-09-06 13:15:26
+    Generated: 2025-09-08 18:12:05
 
     ## Overview
     - **Command**: `ensemble`
-    - **Training Duration**: 1651.54 seconds (27.5 minutes)
-    - **Output Directory**: `output/ensemble_20250906_124755`
+    - **Training Duration**: 6144.87 seconds (102.4 minutes)
+    - **Output Directory**: `output/ensemble_20250908_162940`
 
     ## Dataset Information
-    - **Total Records**: 24,832
-    - **Training Steps per Epoch**: 310
-    - **Validation Steps per Epoch**: 77
+    - **Total Records**: 25,512
+    - **Training Steps per Epoch**: 637
+    - **Validation Steps per Epoch**: 159
 
     ### Vocabulary Sizes
     - **Stations**: 6 unique stations
@@ -19,25 +19,34 @@
 
     ## Training Configuration
     - **Num Models**: 6
-- **Epochs**: 150
-- **Batch Size**: 64
+- **Epochs**: 1000
+- **Batch Size**: 32
 - **Base Learning Rate**: 0.001
-- **Dataset Size**: 24832
+- **Dataset Size**: 25512
+- **Bagging Fraction**: 1.0
+- **Seed Base**: 42
 
 
 ## Final Performance Metrics
-- **Average Validation Loss**: 1.2251
-- **Average Validation Accuracy**: 0.5957
-- **Best Individual Accuracy**: 0.6049
-- **Worst Individual Accuracy**: 0.5812
-- **Ensemble Std Accuracy**: 0.0087
+- **Average Validation Loss**: 0.9233
+- **Average Validation Accuracy**: 0.7460
+- **Best Individual Accuracy**: 0.7720
+- **Worst Individual Accuracy**: 0.7256
+- **Ensemble Std Accuracy**: 0.0181
 
 ## Additional Information
-- **Individual Model Metrics**: {'model_index': 0, 'validation_loss': 1.2142382860183716, 'validation_accuracy': 0.5909090638160706, 'learning_rate': 0.000896730883132793, 'parameters': 53384}, {'model_index': 1, 'validation_loss': 1.2308698892593384, 'validation_accuracy': 0.6049107313156128, 'learning_rate': 0.0011035837511110408, 'parameters': 156552}, {'model_index': 2, 'validation_loss': 1.2147506475448608, 'validation_accuracy': 0.6022727489471436, 'learning_rate': 0.0011871558720145028, 'parameters': 14856}, {'model_index': 3, 'validation_loss': 1.2401705980300903, 'validation_accuracy': 0.5911120176315308, 'learning_rate': 0.0008334328623039442, 'parameters': 14856}, {'model_index': 4, 'validation_loss': 1.2382102012634277, 'validation_accuracy': 0.5811688303947449, 'learning_rate': 0.0009118210339513598, 'parameters': 14856}, {'model_index': 5, 'validation_loss': 1.2121498584747314, 'validation_accuracy': 0.6038960814476013, 'learning_rate': 0.001173992747183349, 'parameters': 14856}
+- **Individual Model Metrics**: {'model_index': 0, 'validation_loss': 0.8818949460983276, 'validation_accuracy': 0.7720125913619995, 'learning_rate': 0.0011677725896206085, 'parameters': 53384}, {'model_index': 1, 'validation_loss': 0.9238271713256836, 'validation_accuracy': 0.7682783007621765, 'learning_rate': 0.0010442193817105285, 'parameters': 156552}, {'model_index': 2, 'validation_loss': 0.9241461753845215, 'validation_accuracy': 0.7399764060974121, 'learning_rate': 0.00096484374873539, 'parameters': 14856}, {'model_index': 3, 'validation_loss': 0.9481979608535767, 'validation_accuracy': 0.7256289124488831, 'learning_rate': 0.0009162122256532111, 'parameters': 14856}, {'model_index': 4, 'validation_loss': 0.9160543084144592, 'validation_accuracy': 0.7421383857727051, 'learning_rate': 0.0008199605784692232, 'parameters': 14856}, {'model_index': 5, 'validation_loss': 0.9454122185707092, 'validation_accuracy': 0.7279874086380005, 'learning_rate': 0.0009672535936195217, 'parameters': 14856}
 - **Ensemble Strategy**: Diverse architectures (deep, wide, standard)
 - **Learning Rate Variation**: 0.8x to 1.2x base rate with random variation
 - **Total Parameters**: 269360
 
+### Temperature Scaling
+- **Temperature**: 1.5000
+- **Uncalibrated Nll**: 1.9108
+- **Calibrated Nll**: 1.8276
+- **Uncalibrated Ece**: 0.0939
+- **Calibrated Ece**: 0.0302
+
 
     ## Dataset Schema
     The model was trained on MBTA track assignment data with the following features: