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` = 16
- `gradient_accumulation_steps` = 1
- `weight_decay` = 1e-09
- `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|
|--|--|--|
|36.309|0.387|1.0|
|36.410|0.393|2.0|
|36.364|0.400|3.0|
|36.109|0.410|4.0|
|36.679|0.391|5.0|
|36.034|0.415|6.0|
|35.636|0.425|7.0|
|35.863|0.412|8.0|
|35.793|0.420|9.0|
|35.573|0.430|10.0|
|35.316|0.439|11.0|
|35.824|0.425|12.0|
|35.705|0.425|13.0|
|35.397|0.434|14.0|
|35.350|0.439|15.0|
|35.182|0.444|16.0|
|35.098|0.445|17.0|
|34.967|0.447|18.0|
|34.875|0.454|19.0|

**Test Accuracy: 0.449**