config.yaml

#GPU
gpu_device_id: 0, #The devices for run this model

# experiment name
exp_name: 'RefNet' #Name for experiment. Logs will be saved in a directory with this name, under log_root

# mode
mode: 'train' # train, val or test

#data_paths #change according to your path
train_path: 'data/mixed_context/finished_files/chunked/train_*'
dev_path: 'data/mixed_context/finished_files/chunked/val_*'
test_path: 'data/mixed_context/finished_files/chunked/test_*'
vocab_path: 'data/mixed_context/finished_files/vocab'

#output paths
log_root: 'log/' #Root directory for all logging.

#Hyperparameters
epoch_num: 20 
hidden_dim: 256 #dimension of RNN hidden states
emb_dim: 128 #dimension of word embeddings
batch_size: 16 #minibatch size'
max_bac_enc_steps: 300 #max timesteps of background encoder (max source background text tokens) Change to 1200 in case of mixed-long
max_con_enc_steps: 65 #max timesteps of context encoder (max source context text tokens)
max_dec_steps: 65 #max timesteps of decoder (max response tokens)
vocab_size: 25000  #'Size of vocabulary. These will be read from the vocabulary file in order. If the vocabulary file contains fewer words than this number, or if this number is set to 0, will take all words in the vocabulary file.
lr: 0.001 #learning rate
rand_unif_init_mag: 0.02 #magnitude for lstm cells random uniform inititalization
trunc_norm_init_std: 1e-4 #std of trunc norm init, used for initializing everything else
max_grad_norm: 2.0 #for gradient clipping
max_span_len: 45 #the max length of predicted span
multi_hop_span_pre_mode: "mlp"
multi_label_eval: False
matching_layer: True
matching_gate: True