Return NaN prediction

[ramdhan1989]

Hi There! I got Nan prediction. I have monthly dataset and would like to forecast 12 steps ahead (1 year). This is my dataset :

this is validation that fed into training as well

this is the model and training :
model = ESRNN(max_epochs=20, freq_of_test=5, batch_size=5, learning_rate=1e-1, per_series_lr_multip=0.8, lr_scheduler_step_size=10, lr_decay=0.1, gradient_clipping_threshold=50, rnn_weight_decay=0.0, level_variability_penalty=100, testing_percentile=10, training_percentile=90, ensemble=True, max_periods=25, seasonality=[], input_size=2, output_size=12,frequency=None, cell_type='LSTM', state_hsize=40, dilations=[[1], [6]], add_nl_layer=False, random_seed=1, device='cpu')

model.fit(training[['unique_id','ds','x']], training[['unique_id','ds','y']],validation[['unique_id','ds','x']],validation[['unique_id','ds','y','y_hat_naive2']],y_hat_benchmark='y_hat_naive2')

I got nan and undetected freq as shown by this during training:

predict return Nan values:

[sd3093]

had the same issue, was due to the ds column not being continuous (i.e. having gaps due to looking at the business days rather than calendar days). maybe that's also related here? do you have any gaps in the ds column?