This repository has the code to run the model my team built for the SQUaD dataset
Please run ./get_started.sh
to download the SQuAD dataset and GloVE Vectors
requirements.txt is used by get_started.sh to install requirements. Once the script is done running, you will have a new directory data with the train and dev json files for SQuAD datset. And another empty folder experiments that will eventually have the results from your experiments.
To run code please run main.py in code. The settings to run BIDAF model are:
python code/main.py --experiment_name=bidaf_best --dropout=0.15 --batch_size=60 --hidden_size_encoder=150 --embedding_size=100 --do_char_embed=False --add_highway_layer=True --rnet_attention=False --bidaf_attention=True --answer_pointer_RNET=False --smart_span=True --hidden_size_modeling=150 --mode=train
The settings to run the RNET model are:
python code/main.py --experiment_name=rnet_best --dropout=0.20 --batch_size=20 --hidden_size_encoder=200 --embedding_size=300 --do_char_embed=False --add_highway_layer=False --rnet_attention=True --bidaf_attention=False --answer_pointer_RNET=True --smart_span=True--mode=official_eval \
--json_in_path=data/tiny-dev.json \
--json_out_path=predictions_rnet.json \
--ckpt_load_dir=experiments/rnet_best/best_checkpoint
Once you run the models, you will have a new folder by the name experiments which will have the results from your code runs
To start tensorboard, please run the following commands:
cd experiments # Go to experiments directory
tensorboard --logdir=. --port=5678 # Start TensorBoard