Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_contiguousf4_20261104-170350

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
train0.35190.83460.76150.61441613.00000.20104058.00000.50003.74963.97050.00000.00000.70210.42003.68813.97050.04000.00000.68930.42003.68144.10790.05000.00000.71080.40683.68064.10790.04240.00000.7167
validation0.7490-0.3448-0.3043-0.0546109.0000-0.0210248.00000.20002.23913.86550.00000.0000-1.23750.10002.38303.86550.02000.0000-1.21850.09002.59333.86550.07000.0000-0.95780.28572.58163.86550.00000.0000-0.7663
test0.4655-0.1808-0.0882-0.1366156.00000.0754149.00000.10002.51203.72680.00000.0000-1.81350.10002.71473.87840.06000.0000-1.58730.12003.08413.90460.08000.0000-0.79230.12502.51673.72680.00000.0000-1.7789

Loss per epoch

training validation

Config

name: reference_avgfp_fc_contiguousf4
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 4
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7