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|
|--|--|--|
|36.424|0.388|1.0|
|36.257|0.398|2.0|
|36.011|0.413|3.0|
|36.333|0.394|4.0|
|36.104|0.406|5.0|
|35.441|0.432|6.0|
|35.057|0.443|7.0|
|35.235|0.434|8.0|
|34.987|0.448|9.0|
|34.987|0.447|10.0|
|34.540|0.464|11.0|
|34.358|0.469|12.0|
|34.304|0.470|13.0|
|34.409|0.466|14.0|
|34.153|0.475|15.0|
|34.440|0.465|16.0|
|34.267|0.473|17.0|
|34.298|0.470|18.0|
|33.984|0.480|19.0|

**Test Accuracy: 0.481**