<filename>Assignment3_for_students/Config.py
UNKNOWN = "UNK"
ROOT = "ROOT"
NULL = "NULL"
NONEXIST = -1


max_iter = 1001
batch_size = 10000

## The length of this list corresponds to the number of hidden layers andtheir sizes
## and the values correspond to the size of each layer
## For eg, [200 ,200] -> 2 hidden layers with 200 nodes each
hidden_size = [200] 

embedding_size = 50
learning_rate = 0.1
display_step = 100
validation_step = 200
n_Tokens = 48
lam = 1e-8

"""
Configuration for the best model 

max_iter = 501
batch_size = 10000
hidden_size = [200] 
embedding_size = 50
learning_rate = 0.003
display_step = 100
validation_step = 500
n_Tokens = 48
lam = 1e-8
"""
<filename>Assignment3_for_students/Config.py
UNKNOWN = "UNK"
ROOT = "ROOT"
NULL = "NULL"
NONEXIST = -1


max_iter = 1001
batch_size = 10000

## The length of this list corresponds to the number of hidden layers andtheir sizes
## and the values correspond to the size of each layer
## For eg, [200 ,200] -> 2 hidden layers with 200 nodes each
hidden_size = [200] 

embedding_size = 50
learning_rate = 0.1
display_step = 100
validation_step = 200
n_Tokens = 48
lam = 1e-8

"""
Configuration for the best model 

max_iter = 501
batch_size = 10000
hidden_size = [200] 
embedding_size = 50
learning_rate = 0.003
display_step = 100
validation_step = 500
n_Tokens = 48
lam = 1e-8
"""
## The length of this list corresponds to the number of hidden layers andtheir sizes ## and the values correspond to the size of each layer ## For eg, [200 ,200] -> 2 hidden layers with 200 nodes each Configuration for the best model   max_iter = 501 batch_size = 10000 hidden_size = [200]  embedding_size = 50 learning_rate = 0.003 display_step = 100 validation_step = 500 n_Tokens = 48 lam = 1e-8