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` = 0.0
- `seed` = 42

Regularization Hyperparameters
- `numerical stability denominator constant` = 0.01
- `lambda` = 0.01
- `alpha` = 2.0
- `beta` = 1.0

Extended Logs:

|eval_loss|eval_accuracy|epoch|
|--|--|--|
|35.436|0.413|1.0|
|35.895|0.412|2.0|
|34.939|0.440|3.0|
|34.845|0.451|4.0|
|35.466|0.432|5.0|
|34.967|0.444|6.0|
|34.487|0.463|7.0|
|35.464|0.429|8.0|
|34.825|0.458|9.0|
|35.149|0.442|10.0|
|35.293|0.442|11.0|
|34.976|0.453|12.0|
|35.004|0.450|13.0|
|35.351|0.441|14.0|
|35.385|0.438|15.0|
|35.321|0.441|16.0|
|35.273|0.441|17.0|
|34.948|0.455|18.0|
|35.225|0.443|19.0|

**Test Accuracy: 0.453**