scheduler = optim.lr_scheduler.OneCycleLR(optimizer, max_lr=hparams['learning_rate'],
steps_per_epoch=int(len(train_loader)),
epochs=hparams['epochs'],
anneal_strategy='linear')
iter_meter = IterMeter()
for epoch in range(1, epochs + 1):
train(model, device, train_loader, criterion, optimizer, scheduler, epoch, iter_meter, experiment)
test(model, device, test_loader, criterion, epoch, iter_meter, experiment)
comet_api_key = "aBJCBXNX82CoOXUaID3DAd4Xk" # add your api key here
project_name = "speechrecognition"
experiment_name = "speechrecognition-colab"
if comet_api_key:
experiment = Experiment(api_key=comet_api_key, project_name=project_name, parse_args=False)
experiment.set_name(experiment_name)
experiment.display()
else:
experiment = Experiment(api_key='dummy_key', disabled=True)
learning_rate = 5e-4
batch_size = 10
epochs = 10
libri_train_set = "train-clean-100"
libri_test_set = "test-clean"
main(learning_rate, batch_size, epochs, libri_train_set, libri_test_set, experiment)
