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` = 0.0
- `seed` = 42

Regularization Hyperparameters
- `numerical stability denominator constant` = 0.01
- `lambda` = 0.0001
- `alpha` = 2.0
- `beta` = 2.0

Extended Logs:

|eval_loss|eval_accuracy|epoch|
|--|--|--|
|34.239|0.403|1.0|
|35.481|0.395|2.0|
|35.944|0.407|3.0|
|35.125|0.438|4.0|
|34.990|0.444|5.0|
|35.375|0.425|6.0|
|34.941|0.449|7.0|
|34.913|0.447|8.0|
|34.559|0.461|9.0|
|34.499|0.464|10.0|
|34.479|0.462|11.0|
|34.368|0.461|12.0|
|34.369|0.464|13.0|
|34.496|0.466|14.0|
|34.358|0.468|15.0|
|34.275|0.469|16.0|
|34.063|0.477|17.0|
|33.969|0.483|18.0|
|33.991|0.478|19.0|

**Test Accuracy: 0.482**