blob: 072a4aeba8b79b421937892ad52fbad157abd4f7 [file] [log] [blame]
[data]
kaldi_root =
train = /home/chiyuan/download/kaldi/egs/ami/s5/exp/sdm1/data-for-mxnet/train.feats
dev = /home/chiyuan/download/kaldi/egs/ami/s5/exp/sdm1/data-for-mxnet/dev.feats
test =
out_file = |
format = kaldi
xdim = 40
ydim = 3920
label_mean = label_mean.feats
[arch]
num_hidden = 1024
# set it to zero if you want a regular LSTM
num_hidden_proj = 512
num_lstm_layer = 3
[train]
batch_size = 40
buckets = 100, 200, 300, 400, 500, 600, 700, 800
num_epoch = 12
# used only if method is truncated-bptt
truncate_len = 20
# gpu0, gpu1
context = gpu0
# bucketing, truncated-bptt
method = truncated-bptt
# checkpoint prefix
prefix = ami
learning_rate = 1
decay_factor = 2
decay_lower_bound = 1e-6
optimizer = speechSGD
momentum = 0.9
# set to 0 to disable gradient clipping
clip_gradient = 0
# uniform, normal, xavier
initializer = Uniform
init_scale = 0.05
weight_decay = 0.008
# show progress every how many batches
show_every = 1000