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config.py
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config.py
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import os
from general_utils import get_logger
class Config():
def __init__(self):
# directory for training outputs
if not os.path.exists(self.output_path):
os.makedirs(self.output_path)
# create instance of logger
self.logger = get_logger(self.log_path)
# general config
output_path = "results/crf/"
model_output = output_path + "model.weights/"
log_path = output_path + "log.txt"
# embeddings
dim = 300
dim_char = 100
glove_filename = "data/glove.6B/glove.6B.{}d.txt".format(dim)
# trimmed embeddings (created from glove_filename with build_data.py)
trimmed_filename = "data/glove.6B.{}d.trimmed.npz".format(dim)
# dataset
dev_filename = "data/coNLL/eng/eng.testa.iob"
test_filename = "data/coNLL/eng/eng.testb.iob"
train_filename = "data/coNLL/eng/eng.train.iob"
max_iter = None # if not None, max number of examples
# vocab (created from dataset with build_data.py)
words_filename = "data/words.txt"
tags_filename = "data/tags.txt"
chars_filename = "data/chars.txt"
# training
train_embeddings = False
nepochs = 15
dropout = 0.5
batch_size = 20
lr_method = "adam"
lr = 0.001
lr_decay = 0.9
clip = -1 # if negative, no clipping
nepoch_no_imprv = 3
reload = False
# model hyperparameters
hidden_size = 300
char_hidden_size = 100
# NOTE: if both chars and crf, only 1.6x slower on GPU
crf = True # if crf, training is 1.7x slower on CPU
chars = True # if char embedding, training is 3.5x slower on CPU