Hi,
I did run the “Estimator” with 2000 epochs, please see below:
specify the DeepAR model
estimator = DeepAREstimator(freq=‘1min’, prediction_length=5, trainer=Trainer(epochs=2000))
fit the model on the training data
predictor = estimator.train(training_data=train_data, validation_data=val_data)
When get to the epoch=1191/2000, I got the error below:
86%|████████▌ | 43/50 [00:02<00:00, 21.32it/s, epoch=1191/2000, avg_epoch_loss=7.6 92%|█████████▏| 46/50 [00:02<00:00, 21.33it/s, epoch=1191/2000, avg_epoch_loss=7.6 98%|█████████▊| 49/50 [00:02<00:00, 21.33it/s, epoch=1191/2000, avg_epoch_loss=7.6100%|██████████| 50/50 [00:02<00:00, 20.91it/s, epoch=1191/2000, avg_epoch_loss=7.61]
1it [00:00, 63.97it/s, epoch=1191/2000, validation_avg_epoch_loss=8.52]
0%| | 0/50 [00:00<?, ?it/s]
Traceback (most recent call last):
File “G:\Python Kalman\gluonts minuto.py”, line 84, in
predictor = estimator.train(training_data=train_data, validation_data=val_data)
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\gluonts\mx\model\estimator.py”, line 238, in train
return self.train_model(
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\gluonts\mx\model\estimator.py”, line 215, in train_model
self.trainer(
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\gluonts\mx\trainer_base.py”, line 410, in call
epoch_loss = loop(
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\gluonts\mx\trainer_base.py”, line 334, in loop
trainer.step(batch_size)
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet\gluon\trainer.py”, line 347, in step
self._update(ignore_stale_grad)
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet\gluon\trainer.py”, line 461, in _update
updater(i, w, g)
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet\optimizer\optimizer.py”, line 2127, in call
self.optimizer.update_multi_precision(i, w, g, self.states[i])
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet\optimizer\optimizer.py”, line 306, in update_multi_precision
self.update(index, weight, grad, state)
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet\optimizer\optimizer.py”, line 1627, in update
adam_update(weight, grad, mean, var, out=weight,
File “”, line 115, in adam_update
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet_ctypes\ndarray.py”, line 82, in _imperative_invoke
check_call(_LIB.MXImperativeInvokeEx(
File “C:\Users\Dalva\AppData\Local\Programs\Python\Python38\Lib\site-packages\mxnet\base.py”, line 246, in check_call
raise get_last_ffi_error()
mxnet.base.MXNetError: MXNetError: Out of range value for lr, value=‘6.018531076210112e-39’, in operator adam_update(name=“”, lr=“6.018531076210112e-39”, beta1=“0.9”, beta2=“0.999”, epsilon=“1e-08”, wd=“1e-08”, rescale_grad=“0.03125”, clip_gradient=“10.0”, lazy_update=“True”)
I did research over the internet, with no success…
Is there anyone who can give a direction ?
Thank you so much