đ swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e-finetuned-og-dataset-10e
This model is a fine - tuned version of Gokulapriyan/swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e on the imagefolder dataset, achieving high accuracy in image classification.
đ Quick Start
This model is a fine - tuned version of Gokulapriyan/swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0556
- Accuracy: 0.9783
⨠Features
- High Accuracy: Achieves an accuracy of 0.9783 on the evaluation set.
- Fine - Tuned: Based on an existing model and fine - tuned on the imagefolder dataset.
đĻ Installation
No installation steps provided in the original document.
đģ Usage Examples
No code examples provided in the original document.
đ Documentation
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: 42
- 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: 2
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| 0.2237 |
1.0 |
546 |
0.0729 |
0.9735 |
| 0.1672 |
2.0 |
1092 |
0.0556 |
0.9783 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
đ License
This project is licensed under the Apache - 2.0 license.
| Property |
Details |
| Model Type |
swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e-finetuned-og-dataset-10e |
| Training Data |
imagefolder |
| Metrics |
accuracy |
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