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vit-base-beans
zazazaChiang/vit-base-beans
vit-base-beans is a image classification model from zazazaChiang. 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
- Aug 31, 2024
- Updated
- Sep 5, 2024
- SHA
- 4f47372c
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-beans
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 0.0667
- Accuracy: 0.9925
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 |
|---|---|---|---|---|
| 0.2797 | 1.0 | 130 | 0.9624 | 0.2229 |
| 0.1283 | 2.0 | 260 | 0.9774 | 0.1240 |
| 0.1325 | 3.0 | 390 | 0.9774 | 0.0953 |
| 0.0809 | 4.0 | 520 | 0.9925 | 0.0667 |
| 0.1164 | 5.0 | 650 | 0.9774 | 0.0842 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Aug 31, 2024
- Updated
- Sep 5, 2024