model = BiLSTM(params)
model.setMappings(mappings, embeddings)
model.setDataset(datasets, data)
model.storeResults("/".join(
[args.root_dir_result, args.directory_name,
"performance.out"])) #Path to store performance scores for dev / test
model.predictionSavePath = "/".join([
args.root_dir_result, args.directory_name, "predictions",
"[ModelName]_[Data].conll"
]) #Path to store predictions
model.modelSavePath = "/".join([
args.root_dir_result, args.directory_name,
"models/[ModelName]_model.h5"
]) #Path to store models
model.fit(epochs=args.nb_epoch)
model.saveParams("/".join(
[args.root_dir_result, args.directory_name, "param"]))
else:
print("Tuning")
drop_out_tuning = [0.25, 0.35, 0.45, 0.5]
for current_drop_out in drop_out_tuning:
params['dropout'] = (current_drop_out, current_drop_out)
model = BiLSTM(params)
model.setMappings(mappings, embeddings)
model.setDataset(datasets, data)
model.storeResults("/".join([
args.root_dir_result, args.directory_name, "performance.out"
])) # Path to store performance scores for dev / test
model.predictionSavePath = "/".join([
args.root_dir_result, args.directory_name, "predictions",
"[ModelName]_[Data].conll"
model.setDataset(datasets, data,
mainModelName=args.target_task) # KHUSUS MULTITSAK
model.storeResults("/".join([
args.root_dir_result, args.directory_name, "performance.out"
])) #Path to store performance scores for dev / test
model.predictionSavePath = "/".join([
args.root_dir_result, args.directory_name, "predictions",
"[ModelName]_[Data].conll"
]) #Path to store predictions
model.modelSavePath = "/".join([
args.root_dir_result, args.directory_name, "models/[ModelName].h5"
]) #Path to store models
model.fit(epochs=args.nb_epoch)
model.saveParams("/".join(
[args.root_dir_result, args.directory_name, "param"]))
else:
for current_run in range(1, args.nb_run + 1):
model = BiLSTM(params)
if args.batch_range is not None:
model.setBatchRangeLength(args.batch_range)
model.setMappings(mappings, embeddings)
model.setDataset(
datasets, data,
mainModelName=args.target_task) # KHUSUS MULTITSAK
model.storeResults("/".join([
args.root_dir_result,
args.directory_name + "_" + str(current_run), "performance.out"
])) # Path to store performance scores for dev / test
