Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_mr5plm_contiguousf1_20261104-222528

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
train1.42280.52950.57510.2302151.0000-0.0776505.00000.3000-0.85120.21730.00000.00000.33430.1000-1.07690.39610.04000.00000.27870.1100-1.04540.76300.06000.00000.31510.1471-0.90540.39610.02940.00000.3511
validation1.69500.33980.31810.110826.0000-0.1528665.00000.0000-1.4383-0.23970.00000.00000.15190.0000-1.8949-0.13520.00000.0000-0.07830.0000-1.7339-0.13520.04000.00000.01110.0000-1.8232-0.23970.00000.0000-0.0344
test1.47380.62500.6699-0.027240.00000.0649254.00000.0000-1.1060-0.01360.00000.00000.08300.0800-0.60690.19870.12000.00000.46470.1000-0.50200.40080.26000.00000.58940.0000-1.0789-0.01360.00000.00000.0972

Loss per epoch

training validation

Config

name: reference_bgl3_fc_mr5plm_contiguousf1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 1
  min_reads: 5
model:
  name: fcn
  hidden:
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7