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` = 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|
|--|--|--|
|1.090|0.375|1.0|
|1.127|0.401|2.0|
|1.127|0.405|3.0|
|1.101|0.428|4.0|
|1.094|0.435|5.0|
|1.096|0.443|6.0|
|1.094|0.444|7.0|
|1.090|0.444|8.0|
|1.080|0.458|9.0|
|1.077|0.463|10.0|
|1.088|0.451|11.0|
|1.079|0.468|12.0|
|1.074|0.471|13.0|
|1.084|0.460|14.0|
|1.080|0.461|15.0|
|1.084|0.462|16.0|
|1.084|0.463|17.0|
|1.083|0.463|18.0|
|1.083|0.461|19.0|

**Test Accuracy: 0.331**