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` = 1.0
- `lambda` = 1.0
- `alpha` = 1.0
- `beta` = 1.0

Extended Logs:

|eval_loss|eval_accuracy|epoch|
|--|--|--|
|1.096|0.427|1.0|
|1.090|0.432|2.0|
|1.077|0.455|3.0|
|1.087|0.443|4.0|
|1.082|0.453|5.0|
|1.085|0.444|6.0|
|1.082|0.448|7.0|
|1.084|0.446|8.0|
|1.088|0.448|9.0|
|1.091|0.444|10.0|
|1.089|0.455|11.0|
|1.084|0.461|12.0|
|1.082|0.458|13.0|
|1.080|0.461|14.0|
|1.080|0.461|15.0|
|1.081|0.454|16.0|
|1.078|0.463|17.0|
|1.078|0.461|18.0|
|1.076|0.469|19.0|

**Test Accuracy: 0.463**