asun17904 / anliR2-t5-base-kd

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Model's Last Updated: February 01 2024

Introduction of anliR2-t5-base-kd

Model Details of anliR2-t5-base-kd

Knowledge Continuity Regularized Network

Dataset: ANLI Round: None

Trainer Hyperparameters:

  • lr = 5e-05
  • per_device_batch_size = 16
  • gradient_accumulation_steps = 1
  • weight_decay = 1e-09
  • seed = 42

Regularization Hyperparameters

  • numerical stability denominator constant = 0.01
  • lambda = 0.001
  • alpha = 2.0
  • beta = 2.0

Extended Logs:

eval_loss eval_accuracy epoch
36.309 0.387 1.0
36.410 0.393 2.0
36.364 0.400 3.0
36.109 0.410 4.0
36.679 0.391 5.0
36.034 0.415 6.0
35.636 0.425 7.0
35.863 0.412 8.0
35.793 0.420 9.0
35.573 0.430 10.0
35.316 0.439 11.0
35.824 0.425 12.0
35.705 0.425 13.0
35.397 0.434 14.0
35.350 0.439 15.0
35.182 0.444 16.0
35.098 0.445 17.0
34.967 0.447 18.0
34.875 0.454 19.0

Test Accuracy: 0.449

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