bosung/knowledge-aug-adv

PyTorch implementation of the paper 'Commonsense Knowledge Augmentation for low-resource languages via adversarial learning' (AAAI21). # knowledge-aug-adv PyTorch implementation of the Commonsense Knowledge Augmentation for low-resource languages via adversarial learning. ## Train Train mBERT: src En, tgt Kr ``` python train_mbert_clip.py \ --target_lang kr \ --src_data_dir data/en_triples \ --tgt_data_dir data/kr_triples \ --do_train \ --do_eval \ --learning_rate 1e-5 \ --batch_size 64 \ --n_critic 1 \ --model_save_file ./save/adv/kr \ --max_epoch 1 \ --clip_lower -1 \ --clip_upper 1 \ --lambd 0.1 \ --dev_file kr_dev.tsv \ --test_file kr_test.tsv \ --max_step 2000 ``` ## Test ``` python train_mbert_clip.py \ --target_lang kr \ --src_data_dir data/en_triples \ --tgt_data_dir data/kr_triples \ --do_eval \ --batch_size 64 \ --test_model {test_model_path} \ --test_file kr_test.tsv ``` ## Data Augmentation ``` python train_mbert_clip.py \ --target_lang kr \ --tgt_data_dir data/kr_triples \ --do_aug \ --test_model {model_path_for_aug} \ --test_file kr_test.tsv ```