This model is a fine-tuned version of bert-large-cased-whole-word-masking on the glue dataset.
It achieves the following results on the evaluation set:
Loss: 0.1725
Accuracy: 0.9438
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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
distributed_type: sagemaker_data_parallel
num_devices: 8
total_train_batch_size: 128
total_eval_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
