Spaces:
Build error
Build error
File size: 1,442 Bytes
cb433d6 |
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 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 |
global:
name: exp
phase: train
stage: pretrain-vision
workdir: /tmp/workdir
seed: ~
dataset:
train: {
roots: ['data/training/MJ/MJ_train/',
'data/training/MJ/MJ_test/',
'data/training/MJ/MJ_valid/',
'data/training/ST'],
batch_size: 128
}
test: {
roots: ['data/evaluation/IIIT5k_3000',
'data/evaluation/SVT',
'data/evaluation/SVTP',
'data/evaluation/IC13_857',
'data/evaluation/IC15_1811',
'data/evaluation/CUTE80'],
batch_size: 128
}
charset_path: data/charset_36.txt
num_workers: 4
max_length: 25 # 30
image_height: 32
image_width: 128
case_sensitive: False
eval_case_sensitive: False
data_aug: True
multiscales: False
pin_memory: True
smooth_label: False
smooth_factor: 0.1
one_hot_y: True
use_sm: False
training:
epochs: 6
show_iters: 50
eval_iters: 3000
save_iters: 20000
start_iters: 0
stats_iters: 100000
optimizer:
type: Adadelta # Adadelta, Adam
true_wd: False
wd: 0. # 0.001
bn_wd: False
args: {
# betas: !!python/tuple [0.9, 0.99], # betas=(0.9,0.99) for AdamW
# betas: !!python/tuple [0.9, 0.999], # for default Adam
}
clip_grad: 20
lr: [1.0, 1.0, 1.0] # lr: [0.005, 0.005, 0.005]
scheduler: {
periods: [3, 2, 1],
gamma: 0.1,
}
model:
name: 'modules.model_abinet.ABINetModel'
checkpoint: ~
strict: True
|