We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Dear SCIANN team
when I use model.train, I use adaptive weight to train, but there is another option which is called as target weight
if I use both, then can these be used simultaneously, or one of them override somehow??
like this
H_model = model.train(input_data, model_target_data, target_weights=[1,1,1,1,10,10,100,100] learning_rate=([0, 10000,20000,30000,40000,50000], [0.001, 0.0005, 0.0001, 0.0001, 0.0001, 0.0001]), batch_size=BATCH_SIZE, epochs=EPOCHS_model, stop_loss_value=1e-8, stop_after=STOP_AFTER, verbose=1, adaptive_weights={'method': 'ntk', 'freq':5000}, )
Best Regards
Seohee Jang
The text was updated successfully, but these errors were encountered:
No branches or pull requests
Dear SCIANN team
when I use model.train, I use adaptive weight to train, but there is another option which is called as target weight
if I use both, then can these be used simultaneously, or one of them override somehow??
like this
H_model = model.train(input_data,
model_target_data,
target_weights=[1,1,1,1,10,10,100,100]
learning_rate=([0, 10000,20000,30000,40000,50000], [0.001, 0.0005, 0.0001, 0.0001, 0.0001, 0.0001]),
batch_size=BATCH_SIZE,
epochs=EPOCHS_model,
stop_loss_value=1e-8,
stop_after=STOP_AFTER,
verbose=1,
adaptive_weights={'method': 'ntk', 'freq':5000},
)
Best Regards
Seohee Jang
The text was updated successfully, but these errors were encountered: