Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_plm_randomf3_20261105-035119

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
train0.04810.97920.87290.95733066.00000.2782127.00000.90003.84664.03070.00000.00000.82700.84003.82434.10680.10000.00000.85090.76003.81104.11360.16000.00000.86390.68523.77714.11450.23460.00000.8858
validation0.06590.97060.86890.94111013.00000.2936336.00000.40003.66863.90810.00000.00000.74380.62003.76734.02680.22000.00000.85160.65003.75744.02680.21000.00000.86710.64813.75714.02680.21300.00000.8697
test0.07640.96590.86350.9319965.00000.3162323.00000.60003.73104.05640.10000.00000.79360.64003.76474.05640.12000.00000.85870.64003.75554.05640.17000.00000.87320.62963.75344.05640.16670.00000.8743

Loss per epoch

training validation

Config

name: reference_avgfp_fc_plm_randomf3
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 3
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