Keras P/R metrics at different thresholds during training
You can see the metrics value for each threshold along the fitting process if you explicitely instantiate the corresponding metric class for each threshold, as follows:
model.compile(
optimizer=keras.optimizers.Adam(learning_rate=1e-2),
loss='categorical_crossentropy',
metrics=[metrics.Recall(thresholds=0.6), 
         metrics.Recall(thresholds=0.9)])

model.fit(X_train, y_train, epochs=10, validation_data=(X_test, y_test))

and as you can see in the image below, for each epoch you can see that the first recall value (with threshold 0.6) is higher than the second one (threshold 0.9) as expected:

And for your case, to build the list of metrics objects programatically, where you can now see 3 recalls per epoch:
thresholds = [0.6, 0.7, 0.9]
metrics_objs_list=[metrics.Recall(thresholds=thr) for thr in thresholds]