This model is a fine-tuned version of bert-base-multilingual-cased on the tmnam20/VieGLUE/MRPC dataset.
It achieves the following results on the evaluation set:
Loss: 0.3703
Accuracy: 0.8358
F1: 0.8775
Combined Score: 0.8566
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: 2e-05
train_batch_size: 32
eval_batch_size: 16
seed: 100
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
