* fix ts api config * fix ts api config
@@ -24,10 +24,10 @@ info_params:
model:
name: Nonstationary_Transformer
model_cfg:
- c_in: 1
- factor: 3
+ c_in: 7
+ factor: 1
p_hidden_dims: [256, 256]
optimizer_params:
learning_rate: 0.0001
gamma: 0.5
- patience: 5
+ patience: 3
@@ -25,7 +25,7 @@ info_params:
name: NonStationary_AD
- c_in: 2
+ c_in: 5
factor: 3
p_hidden_dims: [32, 32]
d_model: 64
@@ -25,17 +25,16 @@ info_params:
name: PatchTSTModel
n_layers: 3
- n_heads: 16
- d_model: 128
- d_ff: 256
- dropout: 0.2
- fc_dropout: 0.2
+ n_heads: 4
+ d_model: 16
+ d_ff: 128
+ dropout: 0.3
+ fc_dropout: 0.3
head_dropout: 0.0
patch_len: 16
stride: 8
- patience: 10
+ patience: 20
- gamma: 0.9
@@ -25,15 +25,15 @@ info_params:
name: TiDE
num_encoder_layers: 2
- use_revin: False
+ use_revin: True
drop_prob: 0.5
- hidden_size: 1024
- decoder_output_dim: 8
- temporal_decoder_hidden: 64
+ hidden_size: 512
+ decoder_output_dim: 32
+ temporal_decoder_hidden: 16
- learning_rate: 0.00099
+ learning_rate: 0.00098
patience: 10
@@ -26,8 +26,8 @@ info_params:
name: TimesNetModel
- c_in: 1 #
- c_out: 1 #
+ c_in: 321 #
+ c_out: 321 #
e_layers: 2 #
num_kernels: 6 #
d_model: 32 #
@@ -25,10 +25,12 @@ info_params:
name: TimesNet_AD
- e_layers: 1
+ e_layers: 2
num_kernels: 6
- d_model: 8
+ d_model: 32
+ d_ff: 64
+ top_k: 3
+ window_sampling_limit: Null
- learning_rate: 0.001
- gamma: 0.5
+ learning_rate: 0.0005
+ gamma: 0.9
@@ -28,15 +28,15 @@ info_params:
name: TimesNet_CLS
- e_layers: 3 #
+ e_layers: 2 #
- d_ff: 32 #
+ d_ff: 64 #
top_k: 3 #
window_sampling_limit: Null #
patience: 10 #
gamma: 0.9
output: 'output/'