metadata
library_name: transformers
base_model: uitnlp/visobert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ViSoBERT_Domain_classifier
results: []
ViSoBERT_Domain_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: 0.0735
- Accuracy: 0.9842
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 |
|---|---|---|---|---|
| No log | 1.0 | 302 | 0.0537 | 0.9807 |
| 0.0737 | 2.0 | 604 | 0.0565 | 0.9839 |
| 0.0737 | 3.0 | 906 | 0.0735 | 0.9842 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.0