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vit-finetuned-chessman2
singlaashish/vit-finetuned-chessman2
vit-finetuned-chessman2 is a image classification model from singlaashish. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Nov 19, 2025
- Updated
- Nov 19, 2025
- SHA
- 0db67d27
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
vit-finetuned-chessman2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2123
- Accuracy: 0.9455
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6072 | 1.0 | 28 | 1.3183 | 0.6 |
| 0.9996 | 2.0 | 56 | 0.7635 | 0.8909 |
| 0.5012 | 3.0 | 84 | 0.4795 | 0.9273 |
| 0.2416 | 4.0 | 112 | 0.3269 | 0.9455 |
| 0.1426 | 5.0 | 140 | 0.2570 | 0.9818 |
| 0.1051 | 6.0 | 168 | 0.2330 | 0.9818 |
| 0.0862 | 7.0 | 196 | 0.2197 | 0.9636 |
| 0.0738 | 8.0 | 224 | 0.2123 | 0.9455 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 19, 2025
- Updated
- Nov 19, 2025