GenomeFlowInterface Settings:
shuffle: True
pos_sampling_rate: 0.05
validation_chroms: ['chr22']
holdout_chroms: ['chr1', 'chr8', 'chr21']
optimizer: adam
learning rate: 0.0003
batch size: 256
epoch size: 2500000
max num of epochs: 100
early stopping metrics: auPRC
early stopping patience: 4

Epoch 1:
Metrics across all datasets:
Balanced Accuracy: 89.94%	auROC: 0.992	 auPRC: 0.403
Recall at 5% | 10% | 25% | 50% FDR: 0.1% | 0.1% | 0.1% | 39.9%	Num Positives: 1135	 Num Negatives: 1022650


New best auPRC. Saving model.


Epoch 2:
Metrics across all datasets:
Balanced Accuracy: 94.15%	auROC: 0.987	 auPRC: 0.121
Recall at 5% | 10% | 25% | 50% FDR: 1.4% | 1.4% | 1.7% | 2.1%	Num Positives: 1135	 Num Negatives: 1022650



Epoch 3:
Metrics across all datasets:
Balanced Accuracy: 65.53%	auROC: 0.778	 auPRC: 0.297
Recall at 5% | 10% | 25% | 50% FDR: 0.4% | 0.4% | 0.4% | 30.9%	Num Positives: 1135	 Num Negatives: 1022650



Epoch 4:
Metrics across all datasets:
Balanced Accuracy: 81.42%	auROC: 0.986	 auPRC: 0.202
Recall at 5% | 10% | 25% | 50% FDR: 0.0% | 0.0% | 0.0% | 0.0%	Num Positives: 1135	 Num Negatives: 1022650



Epoch 5:
Metrics across all datasets:
Balanced Accuracy: 75.73%	auROC: 0.919	 auPRC: 0.393
Recall at 5% | 10% | 25% | 50% FDR: 1.2% | 2.4% | 5.9% | 38.9%	Num Positives: 1135	 Num Negatives: 1022650



Epoch 6:
Metrics across all datasets:
Balanced Accuracy: 84.55%	auROC: 0.965	 auPRC: 0.373
Recall at 5% | 10% | 25% | 50% FDR: 2.7% | 4.1% | 7.3% | 30.8%	Num Positives: 1135	 Num Negatives: 1022650


Finished training after 6 epochs.
The best model's architecture and weights (from epoch 1) were saved to /users/marinovg/2018-01-25-histone-mods/tfdragonn-SequenceAndDNAseAnd6HistoneMarksClassifier_Separate-K562-DNAse-Duke-cuts-11HistoneMarks-SP1/model.arch.json and /users/marinovg/2018-01-25-histone-mods/tfdragonn-SequenceAndDNAseAnd6HistoneMarksClassifier_Separate-K562-DNAse-Duke-cuts-11HistoneMarks-SP1/model.weights.h5