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reapikui_best_model
fadhfaiz/reapikui_best_model
reapikui_best_model is a image classification model from fadhfaiz. 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
- Jun 17, 2024
- Updated
- Jun 18, 2024
- SHA
- 0b52690d
Base models
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. -->
reapikui_best_model
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8426
- Accuracy: 0.922
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.8526 | 0.992 | 62 | 2.6167 | 0.836 |
| 1.7104 | 2.0 | 125 | 1.5818 | 0.884 |
| 1.2318 | 2.992 | 187 | 1.1876 | 0.915 |
| 0.9759 | 4.0 | 250 | 0.9661 | 0.92 |
| 0.8262 | 4.992 | 312 | 0.8780 | 0.92 |
| 0.7681 | 5.952 | 372 | 0.8362 | 0.93 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 17, 2024
- Updated
- Jun 18, 2024