ViSoBERT_Language_classifier

This model is a fine-tuned version of uitnlp/visobert on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0001
• Accuracy: 1.0000

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: 32
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0007	1.0	1700	0.0000	1.0
0.0005	2.0	3400	0.0000	1.0
0.0	3.0	5100	0.0001	1.0000

Framework versions

• Transformers 4.51.3
• Pytorch 2.5.1+cu121
• Datasets 3.6.0
• Tokenizers 0.21.0