Gabriel819/zeroshot_ner

Official code for Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages, EMNLP 2024 main # zeroshot_ner Official code for Zero-Shot Cross-Lingual NER Using Phonemic Representations for Low-Resource Languages, Jimin Sohn*, Haeji Jung*, Alex Cheng, Jooeon Kang, Yilin Du, David R. Mortensen, EMNLP 2024 main *: equal contribution # Approach # Data Structure ``` data ├── id_mapping # 0: 'O', 1: 'B-PER', 2: 'I-PER', 3: 'B-ORG', 4: 'I-ORG', 5: 'B-LOC', 6: 'I-LOC' ├── validation # Validation split ├── tokens # Tokens for mBERT, CANINE, XML-RoBERTa ├── ner_tags # BIO NER tags for mBERT, CANINE, XML-RoBERTa ├── epi_tokens # IPA Tokens for XPhoneBERT, BORT └── epi_ner_tags # BIO IPA NER tags for XPhoneBERT, BORT └── train # Train split ├── tokens ├── ner_tags ├── epi_tokens └── epi_ner_tags ``` # Data - M: mBERT, C: CANINE, X: XPhoneBERT - V represents the languages pre-trained on the model. # Train ``` 1. mBERT train python src/mbert_main.py --task mbert --model bio_mbert --train_language english --max_seq_len 128 --do_train --train_batch_size 128 --eval_batch_size 128 --num_train_epochs 10 2. CANINE train python src/canine_c_main.py --task canine_c --model bio_canine_ch --train_language english --max_seq_len 128 --do_train --train_batch_size 128 --eval_batch_size 128 --num_train_epochs 10 3. XPhoneBERT train python src/xphonebert_main.py --task phoneme_xphonebert --model bio_xphonebert --train_language english --max_seq_len 128 --do_train --train_batch_size 128 --eval_batch_size 128 --num_train_epochs 10 4. BORT train python src/bort_main.py --task phoneme_bort --model bio_bort --train_language english --max_seq_len 128 --do_train --train_batch_size 128 --eval_batch_size 128 --num_train_epochs 10 5. XML RoBERTa train python src/xml_roberta_main.py --task xml_roberta --model bio_xml_roberta --train_language english --max_seq_len 128 --do_train --train_batch_size 128 --eval_batch_size 128 --num_train_epochs 10 ``` # Inference ``` 1. m …