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|
|--|--|--|
|1.099|0.393|1.0|
|1.103|0.405|2.0|
|1.088|0.419|3.0|
|1.083|0.433|4.0|
|1.091|0.429|5.0|
|1.096|0.424|6.0|
|1.094|0.431|7.0|
|1.091|0.434|8.0|
|1.089|0.433|9.0|
|1.095|0.429|10.0|
|1.090|0.440|11.0|
|1.089|0.440|12.0|
|1.093|0.437|13.0|
|1.092|0.440|14.0|
|1.086|0.446|15.0|
|1.095|0.442|16.0|
|1.093|0.431|17.0|
|1.090|0.437|18.0|
|1.091|0.436|19.0|

**Test Accuracy: 0.438**