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Using following commands for prediction
python3 run_ner.py --do_train=false --do_predict=true --do_eval=true --vocab_file=$BIOBERT_DIR/vocab.txt --bert_config_file=$BIOBERT_DIR/bert_config.json --init_checkpoint=$BIOBERT_DIR/model.ckpt-1000000 --num_train_epochs=10.0 --data_dir=$NER_DIR --output_dir=$OUTPUT_DIR
python3 biocodes/ner_detokenize.py --token_test_path=$OUTPUT_DIR/token_test.txt --label_test_path=$OUTPUT_DIR/label_test.txt --answer_path=$NER_DIR/test.tsv --output_dir=$OUTPUT_DIR
perl biocodes/conlleval.pl < $OUTPUT_DIR/NER_result_conll.txt
Also tried with fine tuning and different dataset (NCBI disease, BC4CHEMD, BC2GM) but not able to achieve same accuracy
The text was updated successfully, but these errors were encountered:
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Using following commands for prediction
Also tried with fine tuning and different dataset (NCBI disease, BC4CHEMD, BC2GM) but not able to achieve same accuracy
The text was updated successfully, but these errors were encountered: