anliR3-t5-base – AI Model by asun17904 | AlphaNeural AI

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asun17904/
anliR3-t5-base

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Knowledge Continuity Regularized Network

Dataset: ANLI Round: None

Trainer Hyperparameters:

lr = 5e-05
per_device_batch_size = 32
gradient_accumulation_steps = 1
weight_decay = 1e-09
seed = 42

Regularization Hyperparameters

numerical stability denominator constant = 1.0
lambda = 1.0
alpha = 1.0
beta = 1.0

Extended Logs:

eval_loss	eval_accuracy	epoch
1.110	0.424	1.0
1.098	0.440	2.0
1.104	0.432	3.0
1.096	0.447	4.0
1.098	0.449	5.0
1.106	0.438	6.0
1.109	0.434	7.0
1.097	0.451	8.0
1.086	0.459	9.0
1.094	0.452	10.0
1.100	0.445	11.0
1.104	0.441	12.0
1.092	0.455	13.0
1.087	0.458	14.0
1.092	0.451	15.0
1.092	0.453	16.0
1.089	0.456	17.0
1.083	0.464	18.0
1.089	0.458	19.0

Test Accuracy: 0.460