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* Reorganize example folder * Continue reorganization * Change requirements for tests * Final cleanup * Finish regroup with tests all passing * Copyright * Requirements and readme * Make a full link for the documentation * Address review comments * Apply suggestions from code review Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Add symlink * Reorg again * Apply suggestions from code review Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com> * Adapt title * Update to new strucutre * Remove test * Update READMEs Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
33 lines
848 B
Bash
Executable File
33 lines
848 B
Bash
Executable File
# Script for verifying that run_bart_sum can be invoked from its directory
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# Get tiny dataset with cnn_dm format (4 examples for train, val, test)
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wget https://cdn-datasets.huggingface.co/summarization/cnn_tiny.tgz
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tar -xzvf cnn_tiny.tgz
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rm cnn_tiny.tgz
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export OUTPUT_DIR_NAME=bart_utest_output
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export CURRENT_DIR=${PWD}
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export OUTPUT_DIR=${CURRENT_DIR}/${OUTPUT_DIR_NAME}
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# Make output directory if it doesn't exist
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mkdir -p $OUTPUT_DIR
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# Add parent directory to python path to access lightning_base.py and testing_utils.py
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export PYTHONPATH="../":"${PYTHONPATH}"
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python finetune.py \
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--data_dir=cnn_tiny/ \
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--model_name_or_path=sshleifer/bart-tiny-random \
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--learning_rate=3e-5 \
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--train_batch_size=2 \
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--eval_batch_size=2 \
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--output_dir=$OUTPUT_DIR \
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--num_train_epochs=1 \
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--gpus=0 \
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--do_train "$@"
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rm -rf cnn_tiny
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rm -rf $OUTPUT_DIR
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