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fashion-images-pack-types-vit-large-patch16-224-in21k-v3
touchtech/fashion-images-pack-types-vit-large-patch16-224-in21k-v3
fashion-images-pack-types-vit-large-patch16-224-in21k-v3 is a image classification model from touchtech. 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
- Sep 12, 2023
- Updated
- Sep 13, 2023
- SHA
- 4efad9dc
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. -->
fashion-images-pack-types-vit-large-patch16-224-in21k-v3
This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the touchtech/fashion-images-pack-types dataset. It achieves the following results on the evaluation set:
- Loss: 0.0485
- Accuracy: 0.9908
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.1662 | 1.0 | 1696 | 0.9737 | 0.1074 |
| 0.116 | 2.0 | 3392 | 0.9816 | 0.0545 |
| 0.091 | 3.0 | 5088 | 0.9850 | 0.0647 |
| 0.0601 | 4.0 | 6784 | 0.0502 | 0.9887 |
| 0.0438 | 5.0 | 8480 | 0.0485 | 0.9908 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Sep 12, 2023
- Updated
- Sep 13, 2023