This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tmnam20/VieGLUE/VSFC dataset. It achieves the following results on the evaluation set:

Loss: 0.2167
Accuracy: 0.9501

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: 10
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1744	1.4	500	0.2065	0.9438
0.1043	2.79	1000	0.2169	0.9501

Framework versions

Transformers 4.36.0
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0

tmnam20/mdeberta-v3-base-vsfc-10

mdeberta-v3-base-vsfc-10

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tmnam20/
mdeberta-v3-base-vsfc-10