File size: 1,139 Bytes
b3fb4dd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e34f3c2
b3fb4dd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
Data:
  # Basics
  log_dir: '/data/frugal/logs'
  # Data
  dataset: "KeplerDataset"
  data_dir: '/data/lightPred/data'
  model_name: "CNNEncoder"
  batch_size: 16
  num_epochs: 1000
  exp_num: 2
  max_len_spectra: 4096
  max_days_lc: 270
  lc_freq: 0.0208
  create_umap: True

CNNEncoder:
  # Model
  in_channels: 1
  num_layers: 4
  stride: 1
  encoder_dims: [32,64,128,256]
  kernel_size: 3
  dropout_p: 0.3
  output_dim: 2
  beta: 1
  load_checkpoint: True
  checkpoint_num: 1
  activation: "silu"
  sine_w0: 1.0
  avg_output: True
  checkpoint_path: 'models/frugal_2025-01-10/frugal_cnnencoder_2.pth'

CNNEncoder_f:
  # Model
  in_channels: 1
  num_layers: 4
  stride: 1
  encoder_dims: [32,64,128]
  kernel_size: 3
  dropout_p: 0.3
  output_dim: 2
  beta: 1
  load_checkpoint: True
  checkpoint_num: 1
  activation: "silu"
  sine_w0: 1.0
  avg_output: True


Conformer:
  encoder: ["mhsa_pro", "conv"]
  timeshift: false
  num_layers: 8
  encoder_dim: 128
  num_heads: 8
  kernel_size: 3
  dropout_p: 0.2
  norm: "postnorm"


Optimization:
  # Optimization
  max_lr: 1e-5
  weight_decay: 5e-6
  warmup_pct: 0.3
  steps_per_epoch: 3500