Merge pull request #18 from SCOREC/fix-overfitting

Fixed Overfitting with Dropout Rate, Weight Decay, and on the fly data augmentation.

Author: cwsmith

README.md

@@ -85,10 +85,12 @@ run it
 The classifier supports several command line options for training configuration:
 
 ### Training Parameters
-- `--learningRate`: Learning rate for training (default: 1e-4)
-- `--batchSize`: Batch size for training (default: 8)
-- `--epochs`: Number of training epochs (default: 100)
-- `--minTrainingLoss`: Minimum reduction in training loss in orders of magnitude (default: 2, set to 0 to disable check)
+- `--learningRate`: Learning rate for training (default: 1e-5)
+- `--weightDecay`: Weight decay for L2 regularization (default: 5e-4)
+- `--dropoutRate`: Dropout rate for regularization (default: 0.3)
+- `--batchSize`: Batch size for training (default: 1)
+- `--epochs`: Number of training epochs (default: 2000)
+- `--minTrainingLoss`: Minimum reduction in training loss in orders of magnitude (default: 3, set to 0 to disable check)
 
 ### Data Configuration
 - `--trainFrameFirst`: First frame number for training data (default: 1)
@@ -102,11 +104,13 @@ The classifier supports several command line options for training configuration:
 - `--use-amp`: Enable automatic mixed precision training for faster training on modern GPUs
 - `--amp-dtype`: Data type for mixed precision (`float16` or `bfloat16`, default: `bfloat16`)
 - `--patience`: Patience for early stopping (default: 15 epochs)
+- `--seed`: Random seed for reproducibility (default: None for non-deterministic)
+- `--require-gpu`: Require GPU to be available, exit if not found
 
 ### Output and Monitoring
 - `--plot`: Enable creation of figures showing ground truth and model-identified X-points
 - `--plotDir`: Directory where figures are written (default: `./plots`)
-- `--checkPointFrequency`: Number of epochs between model checkpoints (default: 10)
+- `--checkPointFrequency`: Number of epochs between model checkpoints (default: 100)
 
 ### Performance Benchmarking
 - `--benchmark`: Enable performance benchmarking (tracks timing, throughput, GPU memory)
@@ -118,18 +122,21 @@ The classifier supports several command line options for training configuration:
 
 ### Example with Advanced Options
 
-For faster training with mixed precision and early stopping:
-
+For training with custom regularization and reproducibility:
 ```bash
 python -u ${rcRoot}/reconClassifier/XPointMLTest.py \
 --paramFile=/path/to/params.txt \
 --xptCacheDir=/path/to/cache \
 --epochs 200 \
 --learningRate 1e-4 \
+--weightDecay 1e-3 \
+--dropoutRate 0.3 \
 --batchSize 16 \
 --use-amp \
 --amp-dtype bfloat16 \
 --patience 20 \
+--seed 42 \
+--require-gpu \
 --plot \
 --trainFrameLast 100 \
 --validationFrameLast 120