Update on termination paratemers after tests with larger training set
@@ -38,9 +38,9 @@ class Trainer(object):
self.batch_size = 64 # Maximum batch size
self.max_generator_batches = 32 # Maximum batches of words in a seq to run the generator on in parallel.
self.max_epochs = 40 # Maximum number of training epochs
- self.min_epochs = 8 # Minimum number of training epochs
+ self.min_epochs = 10 # Minimum number of training epochs
self.start_epoch = 1 # The epoch from which to start
- self.min_perplexity_decrement = .03 # If perplexity decrement is lower than this percentage, stop training
+ self.min_perplexity_decrement = .02 # If perplexity decrement is lower than this percentage, stop training
self.param_init = 0.1 # Parameters are initialized over uniform distribution with support
self.optim = 'sgd' # Optimization method. [sgd|adagrad|adadelta|adam]
self.max_grad_norm = 5 # If norm(gradient vector) > max_grad_norm, re-normalize
