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

Loss: 0.2403
Accuracy: 0.9362

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: 1
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
0.1942	1.4	500	0.2416	0.9242
0.1297	2.79	1000	0.2395	0.9337

Framework versions

Transformers 4.35.2
Pytorch 2.2.0.dev20231203+cu121
Datasets 2.15.0
Tokenizers 0.15.0

tmnam20/bert-base-multilingual-cased-vsfc-1

bert-base-multilingual-cased-vsfc-1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tmnam20/
bert-base-multilingual-cased-vsfc-1