# Probabilities in KERAS

I'm struggle with a problem OF class probabilities (binary, 0 and 1). Dont know why but after 100 epoches the probabilities became 0 or 1 (like the class to predict). Maybe something is not working with the code or I missing something?

Train data is 20.000 rows (more or less), test data is 2000 rows. Each row is a match where 0 is lost and 1 is won.

y_train_binary = keras.utils.to_categorical(Y, 2)
y_test_binary = keras.utils.to_categorical(t_Y, 2)
model = Sequential()
model.fit(X, y_train_binary, epochs=300, validation_split=0.2, batch_size=10, verbose=0)
prediction_classes = model.predict_proba(t_X)
numpy.savetxt("C:/Users/Megaport/Desktop/foo.csv", prediction_classes, delimiter=",")


I've tried so many parameters (learning rate, epochs, batch size, epsilon, add layer, less layer, different value of dropout) but the problem is the same: probs are not working.

the probabilities of the class are 1 or 0 and not a value between 1 and 0. This happen after 100 epoches.

data test with prediction after 100 epoches is like this:

**RESULT**   VALUE_A     VALUE_B     VALUE_C    **PRED_0    PRED_1**
0           4          5          3           1          0
0           7          4          5           0          1
1           6          7          6           0          1
1           2          3          4           0          1


What I'm looking for:

**RESULT**   VALUE_A     VALUE_B     VALUE_C    **PRED_0    PRED_1**
0           4          5          3           0.65          0.35
0           7          4          5           0.25          0.75
1           6          7          6           0.20          0.80
1           2          3          4           0.30          0.70


Plus, someone could please give me some advice looking at accuracy and loss graph?

y_pred = estimator.predict_proba(X.drop(columns=self.drop_columns))