This model is a fine-tuned version of bert-base-uncased on the ComNum dataset.
This model used 800 samples as training, 200 as validation, and 1200 as test on three epochs.
It achieves the following results on the evaluation set:
Loss: 0.3675
Accuracy: 0.7175
This model achieves the following results on the test set:
Loss: 0.3475
Accuracy: 0.7493
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
