oov_token=1,
sos_token=2,
eos_token=3,
max_size=30) # max size of generated sentence in prediction mode
model.fit(training_set,
test_set,
lr=0.001,
batch_size=64,
n_epochs=20,
patience=2)
model.save(path_to_save_models + 'my_model.pt')
else:
model = seq2seqModel.load(path_to_save_models + 'pretrained_moodle.pt')
to_test = [
'I am a student.',
'I have a red car.', # inversion captured
'I love playing video games.',
'This river is full of fish.', # plein vs pleine (accord)
'The fridge is full of food.',
'The cat fell asleep on the mat.',
'my brother likes pizza.', # pizza is translated to 'la pizza'
'I did not mean to hurt you', # translation of mean in context
'She is so mean',
'Help me pick out a tie to go with this suit!', # right translation
"I can't help but smoking weed", # this one and below: hallucination
'The kids were playing hide and seek',
'The cat fell asleep in front of the fireplace'
oov_token=1,
sos_token=2,
eos_token=3,
max_size=30) # max size of generated sentence in prediction mode
model.fit(training_set,
test_set,
lr=0.001,
batch_size=64,
n_epochs=2,
patience=2)
model.save(path_to_save_models + 'my_model.pt')
else:
model = seq2seqModel.load(path_to_save_models + 'pretrained_moodle.pt',
vocab_source_inv)
to_test = [
'I am a student',
'I have a red car.', # inversion captured
'I love playing video games.',
'This river is full of fish.', # plein vs pleine (accord)
'The fridge is full of food.',
'The cat fell asleep on the mat.',
'my brother likes pizza.', # pizza is translated to 'la pizza'
'I did not mean to hurt you', # translation of mean in context
'She is so mean',
'Help me pick out a tie to go with this suit!', # right translation
"I can't help but smoking weed", # this one and below: hallucination
'The kids were playing hide and seek',
'The cat fell asleep in front of the fireplace'