Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_plm_contiguousf2_20261104-184337

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
train0.21230.88830.83010.7890835.00000.1398137.00000.20003.65353.88380.00000.00000.70010.40003.68463.93630.04000.00000.76950.43003.67673.93630.06000.00000.78670.38893.67973.93630.04170.00000.7771
validation0.2763-0.0754-0.0915-0.1671366.00000.10751033.00000.00003.22653.71060.00000.0000-0.56900.20003.31124.02120.02000.0000-0.53290.19003.36414.02120.02000.0000-0.45530.00003.28803.71060.00000.0000-0.4692
test0.53780.02430.0128-0.0774142.0000-0.044925.00000.10002.53193.80420.00000.0000-1.32650.14003.15203.96120.08000.0000-0.33690.18003.25663.96120.15000.0000-0.14440.09092.42003.80420.00000.0000-1.5271

Loss per epoch

training validation

Config

name: reference_avgfp_fc_plm_contiguousf2
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 2
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