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eda07efaa5
* Add more token classification examples * POS tagging example * Phrase chunking example * PR review fixes * Add conllu to third party list (used in token classification examples)
40 lines
1.1 KiB
Bash
Executable File
40 lines
1.1 KiB
Bash
Executable File
#!/usr/bin/env bash
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if ! [ -f ./dev.txt ]; then
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echo "Download dev dataset...."
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curl -L -o ./dev.txt 'https://github.com/UniversalDependencies/UD_English-EWT/raw/master/en_ewt-ud-dev.conllu'
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fi
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if ! [ -f ./test.txt ]; then
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echo "Download test dataset...."
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curl -L -o ./test.txt 'https://github.com/UniversalDependencies/UD_English-EWT/raw/master/en_ewt-ud-test.conllu'
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fi
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if ! [ -f ./train.txt ]; then
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echo "Download train dataset...."
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curl -L -o ./train.txt 'https://github.com/UniversalDependencies/UD_English-EWT/raw/master/en_ewt-ud-train.conllu'
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fi
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export MAX_LENGTH=200
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export BERT_MODEL=bert-base-uncased
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export OUTPUT_DIR=postagger-model
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export BATCH_SIZE=32
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export NUM_EPOCHS=3
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export SAVE_STEPS=750
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export SEED=1
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# Add parent directory to python path to access lightning_base.py
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export PYTHONPATH="../":"${PYTHONPATH}"
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python3 run_pl_ner.py --data_dir ./ \
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--task_type POS \
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--model_name_or_path $BERT_MODEL \
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--output_dir $OUTPUT_DIR \
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--max_seq_length $MAX_LENGTH \
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--num_train_epochs $NUM_EPOCHS \
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--train_batch_size $BATCH_SIZE \
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--seed $SEED \
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--gpus 1 \
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--do_train \
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--do_predict
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