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makefile
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device=0
lr=0.9
train-classification:
python sse_train.py --task_type=classification --data_dir=rawdata-classification --model_dir=models-classification --device=$(device) --learning_rate=$(lr) --max_epoc=50 --steps_per_checkpoint=200
index-classification:
python sse_index.py --idx_model_dir=models-classification --idx_rawfilename=targetIDs --idx_encodedIndexFile=targetEncodingIndex.tsv
visualize-classification:
python sse_visualize.py models-classification/targetEncodingIndex.tsv models-classification/SSE-Visualization.png
demo-classification:
python sse_demo.py 10 --model_dir=models-classification --indexFile=targetEncodingIndex.tsv
train-qna:
python sse_train.py --task_type=qna --data_dir=rawdata-qna --model_dir=models-qna --batch_size=32 --max_epoc=200 --steps_per_checkpoint=10 --device=$(device) --learning_rate=$(lr) --vocab_size=8000 --max_seq_length=1000
demo-qna:
python sse_demo.py 10 --model_dir=models-qna --indexFile=targetEncodingIndex.tsv
index-qna:
python sse_index.py --idx_model_dir=models-qna --idx_rawfilename=targetIDs --idx_encodedIndexFile=targetEncodingIndex.tsv
visualize-qna:
python sse_visualize.py models-qna/targetEncodingIndex.tsv models-qna/SSE-Visualization.png
train-ranking:
python sse_train.py --task_type=ranking --data_dir=rawdata-ranking --model_dir=models-ranking --device=$(device) --learning_rate=$(lr) --embedding_size=30 --encoding_size=64 --max_seq_length=60 --batch_size=32 --max_epoc=200 --steps_per_checkpoint=200
index-ranking:
python sse_index.py --idx_model_dir=models-ranking --idx_rawfilename=targetIDs --idx_encodedIndexFile=targetEncodingIndex.tsv
demo-ranking:
python sse_demo.py 10 --model_dir=models-ranking --indexFile=targetEncodingIndex.tsv
visualize-ranking:
python sse_visualize.py models-ranking/targetEncodingIndex.tsv models-ranking/SSE-Visualization.png
train-crosslingual:
python sse_train.py --task_type=crosslingual --data_dir=rawdata-crosslingual --model_dir=models-crosslingual --device=$(device) --learning_rate=$(lr) --embedding_size=40 --encoding_size=50 --max_seq_length=50 --batch_size=32 --max_epoc=1000 --steps_per_checkpoint=200 --network_mode=shared-encoder
index-crosslingual:
python sse_index.py --idx_model_dir=models-crosslingual --idx_rawfilename=targetIDs --idx_encodedIndexFile=targetEncodingIndex.tsv
visualize-crosslingual:
python sse_visualize.py models-crosslingual/targetEncodingIndex.tsv models-crosslingual/SSE-Visualization.png
demo-crosslingual:
python sse_demo.py 10 --model_dir=models-crosslingual --indexFile=targetEncodingIndex.tsv
clean:
rm -rf models*
rm *.pyc
rm -rf __pycache__