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` = 1e-09
- `seed` = 42

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

Extended Logs:

|eval_loss|eval_accuracy|epoch|
|--|--|--|
|1.139|0.394|1.0|
|1.142|0.396|2.0|
|1.146|0.388|3.0|
|1.152|0.388|4.0|
|1.122|0.417|5.0|
|1.127|0.415|6.0|
|1.117|0.428|7.0|
|1.118|0.428|8.0|
|1.113|0.433|9.0|
|1.101|0.440|10.0|
|1.103|0.440|11.0|
|1.104|0.442|12.0|
|1.105|0.439|13.0|
|1.096|0.449|14.0|
|1.102|0.445|15.0|
|1.106|0.437|16.0|
|1.102|0.446|17.0|
|1.104|0.443|18.0|
|1.099|0.447|19.0|

**Test Accuracy: 0.447**