/AA-code

Primary LanguagePython

Adaptive Adpater Appraisal

Paper

Task and Sentiment Adaptation for Appraisal Tagging

Data and Resource

We use SOCC and POST datasets for rumour detection.

In this repository, we links to the public available dataset SOCC. Please git clone In this repository, we do not provide you with the raw input data. Please download the datasets from the following links.

Dataset Link
SOCC https://github.com/sfu-discourse-lab/SOCC )

Dependencies

  1. Python 3.6
  2. Run pip install -r requirements.txt

Pre-training LM script:

Clone the transformer to local directory

git clone https://github.com/huggingface/transformers.git

For further pre-training the language models:

python transformers/examples/language-modeling/run_language_modeling.py ,
        --output_dir='ML_MBERT_TAPT',
        --model_type=bert ,
        --model_name_or_path=bert-base-multilingual-cased,
        --do_train,
        --overwrite_output_dir,
        --train_data_file='train.txt',
        --do_eval,
        --block_size=256,
        --eval_data_file='vali.txt',
        --mlm"

#If you find this code useful, please let us know and cite our paper.