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| # | |
| # Copyright (c) 2016-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. | |
| # | |
| # This script applies quantization to the models from Table 1 in: | |
| # Bag of Tricks for Efficient Text Classification, arXiv 1607.01759, 2016 | |
| set -e | |
| DATASET=( | |
| ag_news | |
| sogou_news | |
| dbpedia | |
| yelp_review_polarity | |
| yelp_review_full | |
| yahoo_answers | |
| amazon_review_full | |
| amazon_review_polarity | |
| ) | |
| # These learning rates were chosen by validation on a subset of the training set. | |
| LR=( 0.25 0.5 0.5 0.1 0.1 0.1 0.05 0.05 ) | |
| RESULTDIR=result | |
| DATADIR=data | |
| echo 'Warning! Make sure you run the classification-results.sh script before this one' | |
| echo 'Otherwise you can expect the commands in this script to fail' | |
| for i in {0..7} | |
| do | |
| echo "Working on dataset ${DATASET[i]}" | |
| ../../fasttext quantize -input "${DATADIR}/${DATASET[i]}.train" \ | |
| -output "${RESULTDIR}/${DATASET[i]}" -lr "${LR[i]}" \ | |
| -thread 4 -qnorm -retrain -epoch 5 -cutoff 100000 > /dev/null | |
| ../../fasttext test "${RESULTDIR}/${DATASET[i]}.ftz" \ | |
| "${DATADIR}/${DATASET[i]}.test" | |
| done | |