bgl3 · Sequence CNN

reference_bgl3_cnn_plm_randomf2_20261104-182335

Metrics

Set	mse	pearsonr	spearmanr	r2	above_wt_n	above_wt_spearmanr	budget_to_max	hit_rate_at_10	mean_at_10	max_at_10	captured_at_10	hit_rate_at_50	mean_at_50	max_at_50	precision_at_50	captured_at_50	hit_rate_at_100	mean_at_100	max_at_100	precision_at_100	captured_at_100	hit_rate_at_1pct	mean_at_1pct	max_at_1pct	precision_at_1pct	captured_at_1pct
train	1.0296	0.6853	0.6436	0.4685	6114.0000	0.2621	4198.0000	1.0000	1.3490	1.7856	0.4818	1.0000	1.4569	3.1160	0.0200	0.5845	0.9800	1.3999	3.1160	0.0500	0.6025	0.9625	1.3604	3.1160	0.0875	0.6150
validation	1.3064	0.5810	0.5389	0.3331	2110.0000	0.1416	378.0000	0.8000	0.6061	1.7856	0.3019	0.8000	0.7896	2.5002	0.0200	0.4071	0.8200	0.8405	2.6204	0.0400	0.4498	0.8113	0.8305	2.5002	0.0189	0.4245
test	1.4005	0.5611	0.5247	0.3106	2044.0000	0.1458	1449.0000	1.0000	1.1908	2.0841	0.4973	0.9000	1.0161	2.4567	0.0200	0.4957	0.8700	0.9361	2.4567	0.0600	0.4980	0.9057	1.0085	2.4567	0.0189	0.4956

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_plm_randomf2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 2
model:
  name: cnn
  conv:
  - - 32
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7