/
config.yaml
29 lines (26 loc) · 1.14 KB
/
config.yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
cuda: True
seed: 1111 #random seed
class_number: 5 #number of classes
model:
emsize: 200 #size of word embeddings
nhid: 300 #number of hidden units per layer
nlayers: 2 #number of layers in BiLSTM
attention_unit: 350 #number of attention unit
attention_hops: 4 #number of attention hops, for multi-hop attention model
dropout: 0.5 #dropout applied to layers (0 = no dropout)
clip: 0.5 #clip to prevent the too large grad in LSTM
nfc: 300 #hidden (fully connected) layer size for classifier MLP
training:
lr: .001 #initial learning rate
optimizer: 'Adam' #type of optimizer
epochs: 5 #upper epoch limit
log_interval: 20 #report interval
batch_size: 50 #batch size for training
penalization_coeff: 1 #the penalization coefficient
data:
save: #path to save the final model
dictionary: #path to save the dictionary, for faster corpus loading
word_vector: #path for pre-trained word vectors (e.g. GloVe), should be a PyTorch model.
train_data: #location of the training data, should be a json file
val_data: #location of the development data, should be a json file
test_data: #location of the test data, should be a json file