Protein Engineering

avgfp · Graph CNN

reference_avgfp_gcn_contiguousf4_20261104-170353

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
train0.76230.61850.60280.16471613.00000.06962942.00000.30003.29233.85240.00000.00000.27280.34003.40453.93740.00000.00000.40450.26003.42914.01080.03000.00000.44690.25423.36034.01080.03390.00000.3786
validation0.68480.52860.36850.0357109.0000-0.1427455.00000.10003.59223.74880.00000.00000.54870.04003.36493.77420.02000.00000.28920.10003.37473.87400.10000.00000.32550.14293.58653.74880.00000.00000.5280
test0.46130.41990.3138-0.1263156.00000.1202619.00000.10002.48983.73770.00000.0000-1.85880.10003.22583.83390.02000.0000-0.40580.24003.42963.86270.16000.00000.07070.00002.20773.65420.00000.0000-2.4001

Loss per epoch

training validation

Config

name: reference_avgfp_gcn_contiguousf4
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 4
model:
  name: gcn
  filters:
  - 128
  - 128
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7