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` = 1
- `weight_decay` = 0.0
- `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|
|--|--|--|
|37.124|0.356|1.0|
|35.453|0.414|2.0|
|36.455|0.393|3.0|
|35.682|0.417|4.0|
|36.248|0.397|5.0|
|35.343|0.431|6.0|
|35.734|0.413|7.0|
|35.896|0.414|8.0|
|35.431|0.434|9.0|
|35.405|0.425|10.0|
|34.976|0.445|11.0|
|35.522|0.434|12.0|
|35.389|0.436|13.0|
|35.805|0.422|14.0|
|35.435|0.434|15.0|
|35.751|0.423|16.0|
|35.567|0.430|17.0|
|35.204|0.439|18.0|
|35.490|0.430|19.0|

**Test Accuracy: 0.430**