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