metadata
library_name: transformers
license: apache-2.0
base_model: Visual-Attention-Network/van-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SPIE_MULTICLASS_CHINA_2_4
results: []
SPIE_MULTICLASS_CHINA_2_4
This model is a fine-tuned version of Visual-Attention-Network/van-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3826
- Accuracy: 0.8851
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7717 | 0.96 | 18 | 1.1875 | 0.68 |
| 0.953 | 1.9733 | 37 | 0.6558 | 0.8175 |
| 0.5564 | 2.9867 | 56 | 0.4640 | 0.8642 |
| 0.4218 | 4.0 | 75 | 0.3893 | 0.8838 |
| 0.3865 | 4.8 | 90 | 0.3826 | 0.8851 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0