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vit-finetuned-chessman2
gvinay4362/vit-finetuned-chessman2
vit-finetuned-chessman2 is a image classification model from gvinay4362. 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
- 336398e8
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 trpakov/vit-face-expression on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2361
- Accuracy: 0.9591
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 |
|---|---|---|---|---|
| 0.1287 | 1.0 | 110 | 0.1899 | 0.9455 |
| 0.0386 | 2.0 | 220 | 0.2242 | 0.95 |
| 0.0116 | 3.0 | 330 | 0.3516 | 0.9227 |
| 0.0113 | 4.0 | 440 | 0.2361 | 0.9591 |
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