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vit-bmr-tuned
jmoriwa/vit-bmr-tuned
vit-bmr-tuned is a image classification model from jmoriwa. 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
- Oct 29, 2025
- Updated
- Oct 31, 2025
- SHA
- f6ca8d38
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-bmr-tuned
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: 0.5646
- Accuracy: 0.8765
- Precision: 0.9023
- Recall: 0.8765
- F1: 0.8756
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: 4
- eval_batch_size: 8
- 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: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 160 | 0.4052 | 0.8395 | 0.8515 | 0.8395 | 0.8392 |
| No log | 2.0 | 320 | 0.3068 | 0.9012 | 0.9012 | 0.9012 | 0.9012 |
| No log | 3.0 | 480 | 0.4265 | 0.8765 | 0.8860 | 0.8765 | 0.8764 |
| 0.3298 | 4.0 | 640 | 0.6281 | 0.8519 | 0.8646 | 0.8519 | 0.8494 |
| 0.3298 | 5.0 | 800 | 0.5646 | 0.8765 | 0.9023 | 0.8765 | 0.8756 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Oct 29, 2025
- Updated
- Oct 31, 2025