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vit_finetune_mask
Kai1014/vit_finetune_mask
vit_finetune_mask is a image classification model from Kai1014. 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
- Mar 29, 2024
- Updated
- Mar 29, 2024
- SHA
- f2f789b3
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_finetune_mask
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: 0.0966
- Accuracy: 0.9716
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1378 | 0.98 | 23 | 0.1374 | 0.9716 |
| 0.0887 | 2.0 | 47 | 0.0863 | 0.9886 |
| 0.0662 | 2.98 | 70 | 0.0724 | 0.9830 |
| 0.0677 | 4.0 | 94 | 0.0975 | 0.9659 |
| 0.0691 | 4.89 | 115 | 0.0966 | 0.9716 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 29, 2024
- Updated
- Mar 29, 2024