pytorch en license:mit region:us
---
language: en
license: mit
library_name: pytorch
---
# 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` = 1.0
- `lambda` = 1.0
- `alpha` = 1.0
- `beta` = 1.0

Extended Logs:

|eval_loss|eval_accuracy|epoch|
|--|--|--|
|1.176|0.364|1.0|
|1.142|0.393|2.0|
|1.140|0.402|3.0|
|1.143|0.396|4.0|
|1.125|0.412|5.0|
|1.152|0.392|6.0|
|1.134|0.407|7.0|
|1.140|0.407|8.0|
|1.128|0.420|9.0|
|1.145|0.393|10.0|
|1.117|0.431|11.0|
|1.122|0.426|12.0|
|1.111|0.434|13.0|
|1.130|0.418|14.0|
|1.122|0.428|15.0|
|1.115|0.431|16.0|
|1.110|0.437|17.0|
|1.104|0.440|18.0|
|1.094|0.450|19.0|

**Test Accuracy: 0.456**