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python/doc/examples/train_supervised.py
43 строки
1 KB
Onur Çelebi
scripts to download word vector models and reduce their size
03 янв 2020, 15:37
03 янв 2020, 15:37
02c61ef
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О чём код?
#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # All rights reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import os from fasttext import train_supervised def print_results(N, p, r): print("N\t" + str(N)) print("P@{}\t{:.3f}".format(1, p)) print("R@{}\t{:.3f}".format(1, r)) if __name__ == "__main__": train_data = os.path.join(os.getenv("DATADIR", ''), 'cooking.train') valid_data = os.path.join(os.getenv("DATADIR", ''), 'cooking.valid') # train_supervised uses the same arguments and defaults as the fastText cli model = train_supervised( input=train_data, epoch=25, lr=1.0, wordNgrams=2, verbose=2, minCount=1 ) print_results(*model.test(valid_data)) model = train_supervised( input=train_data, epoch=25, lr=1.0, wordNgrams=2, verbose=2, minCount=1, loss="hs" ) print_results(*model.test(valid_data)) model.save_model("cooking.bin") model.quantize(input=train_data, qnorm=True, retrain=True, cutoff=100000) print_results(*model.test(valid_data)) model.save_model("cooking.ftz")