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Knowledge Continuity Regularized Network

Dataset: ANLI Round: None

Trainer Hyperparameters:

  • lr = 5e-05
  • per_device_batch_size = 8
  • gradient_accumulation_steps = 2
  • weight_decay = 1e-09
  • seed = 42

Regularization Hyperparameters

  • numerical stability denominator constant = 0.01
  • lambda = 0.01
  • alpha = 2.0
  • beta = 2.0

Extended Logs:

eval_loss eval_accuracy epoch
22.099 0.350 1.0
22.046 0.400 2.0
21.908 0.400 3.0
21.955 0.400 4.0
22.005 0.400 5.0
22.104 0.400 6.0
22.253 0.400 7.0
22.441 0.400 8.0
22.574 0.400 9.0
22.605 0.400 10.0
22.551 0.400 11.0
22.509 0.400 12.0
22.607 0.400 13.0
22.663 0.400 14.0
22.797 0.400 15.0
22.860 0.400 16.0
22.913 0.400 17.0
22.923 0.400 18.0
22.924 0.400 19.0
22.915 0.400 20.0
22.938 0.400 21.0
23.008 0.400 22.0
23.005 0.400 23.0
23.025 0.400 24.0
23.082 0.400 25.0
23.077 0.400 26.0
23.082 0.400 27.0
23.042 0.400 28.0
23.036 0.400 29.0
23.062 0.400 30.0
23.071 0.400 31.0
23.068 0.400 32.0
23.080 0.400 33.0
23.127 0.400 34.0
23.276 0.400 35.0
23.254 0.400 36.0
23.235 0.400 37.0
23.298 0.400 38.0
23.186 0.400 39.0
23.164 0.400 40.0
23.157 0.400 41.0
23.215 0.400 42.0
23.208 0.400 43.0
23.219 0.400 44.0
23.199 0.400 45.0
23.186 0.400 46.0
23.149 0.400 47.0
23.252 0.400 48.0
23.162 0.400 49.0
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