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vit-snack-classification-fp16
MONYETTERBANG/vit-snack-classification-fp16
vit-snack-classification-fp16 is a image classification model from MONYETTERBANG. 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
- Feb 28, 2024
- Updated
- Feb 28, 2024
- SHA
- f195a018
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. -->
vit-snack-classification-fp16
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: 0.2106
- Accuracy: 0.9539
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2332 | 0.33 | 100 | 0.2636 | 0.9309 |
| 0.1996 | 0.66 | 200 | 0.3591 | 0.9110 |
| 0.1995 | 0.99 | 300 | 0.3087 | 0.9194 |
| 0.1388 | 1.32 | 400 | 0.2386 | 0.9414 |
| 0.1304 | 1.65 | 500 | 0.2730 | 0.9309 |
| 0.1606 | 1.98 | 600 | 0.3044 | 0.9215 |
| 0.1067 | 2.31 | 700 | 0.2363 | 0.9435 |
| 0.0992 | 2.64 | 800 | 0.2666 | 0.9393 |
| 0.0976 | 2.97 | 900 | 0.2698 | 0.9382 |
| 0.1091 | 3.3 | 1000 | 0.2390 | 0.9487 |
| 0.1085 | 3.63 | 1100 | 0.2446 | 0.9487 |
| 0.1046 | 3.96 | 1200 | 0.2331 | 0.9414 |
| 0.119 | 4.29 | 1300 | 0.2156 | 0.9508 |
| 0.1233 | 4.62 | 1400 | 0.2179 | 0.9508 |
| 0.1186 | 4.95 | 1500 | 0.2106 | 0.9539 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Feb 28, 2024
- Updated
- Feb 28, 2024