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|
|--|--|--|
|1.110|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**