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vit-base-patch16-224-in21k-YB
lngrid2020/vit-base-patch16-224-in21k-YB
vit-base-patch16-224-in21k-YB is a image classification model from lngrid2020. 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
- Dec 18, 2023
- Updated
- Dec 26, 2023
- SHA
- 89f540cf
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-base-patch16-224-in21k-YB
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: 0.3922
- Accuracy: 0.8220
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5973 | 0.49 | 100 | 0.4747 | 0.7797 |
| 0.4672 | 0.99 | 200 | 0.4363 | 0.7979 |
| 0.3914 | 1.48 | 300 | 0.4090 | 0.8115 |
| 0.3749 | 1.97 | 400 | 0.4001 | 0.8189 |
| 0.3281 | 2.47 | 500 | 0.4023 | 0.8183 |
| 0.3187 | 2.96 | 600 | 0.3922 | 0.8220 |
Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Dec 18, 2023
- Updated
- Dec 26, 2023