CML test

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ML Model Training Report

Model Performance Metrics

Model Performance Metrics
Mean Absolute Error = 61.03
Mean Squared Error = 4675.56

Model Results Visualization

Training Summary

• Model: TensorFlow Sequential Neural Network
• Architecture: Dense(10, relu) -> Dense(1)
• Optimizer: Adam (lr=0.01)
• Loss: Mean Squared Error
• Epochs: 100
• Dataset: Linear regression (50 samples, 50/50 train/test split)

[github-actions]

ML Model Training Report

Model Performance Metrics

Model Performance Metrics

Mean Absolute Error = 0.000709
Mean Squared Error = 0.000001
R² Score = 1.000000
Final Training Loss = 4.62e-10
Final Validation Loss = 1.89e-10
Training Samples = 35
Test Samples = 15
Model Architecture = Single Dense Layer
Optimizer = Adam (lr=0.1)
Training Status = ✅ EXCELLENT PERFORMANCE

Model Results Visualization

Training Summary

• Model: TensorFlow Sequential Neural Network
• Architecture: Dense(10, relu) -> Dense(1)
• Optimizer: Adam (lr=0.01)
• Loss: Mean Squared Error
• Epochs: 100
• Dataset: Linear regression (50 samples, 50/50 train/test split)

[github-actions]

ML Model Training Report

Model Performance Metrics

Model Performance Metrics

Mean Absolute Error = 0.004120
Mean Squared Error = 0.000022
R² Score = 1.000000
Final Training Loss = 8.60e-09
Final Validation Loss = 6.59e-09
Training Samples = 35
Test Samples = 15
Model Architecture = Single Dense Layer
Optimizer = Adam (lr=0.1)
Training Status = ✅ EXCELLENT PERFORMANCE

Model Results Visualization

Training Summary

• Model: TensorFlow Sequential Neural Network
• Architecture: Dense(10, relu) -> Dense(1)
• Optimizer: Adam (lr=0.01)
• Loss: Mean Squared Error
• Epochs: 100
• Dataset: Linear regression (50 samples, 50/50 train/test split)