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|
|--|--|--|
|35.259|0.429|1.0|
|35.007|0.437|2.0|
|35.542|0.430|3.0|
|35.120|0.436|4.0|
|35.506|0.427|5.0|
|35.583|0.422|6.0|
|35.422|0.438|7.0|
|35.326|0.437|8.0|
|34.973|0.449|9.0|
|34.880|0.448|10.0|
|34.993|0.446|11.0|
|35.145|0.442|12.0|
|35.070|0.448|13.0|
|35.162|0.442|14.0|
|35.300|0.443|15.0|
|35.165|0.443|16.0|
|34.973|0.448|17.0|
|34.877|0.450|18.0|
|35.098|0.451|19.0|

**Test Accuracy: 0.447**