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vit-base-patch16-224-in21k-finetuned
b07611031/vit-base-patch16-224-in21k-finetuned
vit-base-patch16-224-in21k-finetuned is a image classification model from b07611031. 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 3, 2024
- Updated
- Mar 3, 2024
- SHA
- 8302d410
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-finetuned
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: 0.0051
- Accuracy: 1.0
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: 10
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 90 | 0.1809 | 0.9911 |
| No log | 2.0 | 180 | 0.0815 | 0.9911 |
| No log | 3.0 | 270 | 0.0542 | 0.9911 |
| No log | 4.0 | 360 | 0.0298 | 1.0 |
| No log | 5.0 | 450 | 0.0312 | 0.9955 |
| 0.1429 | 6.0 | 540 | 0.0235 | 1.0 |
| 0.1429 | 7.0 | 630 | 0.0196 | 1.0 |
| 0.1429 | 8.0 | 720 | 0.0154 | 1.0 |
| 0.1429 | 9.0 | 810 | 0.0145 | 1.0 |
| 0.1429 | 10.0 | 900 | 0.0125 | 1.0 |
| 0.1429 | 11.0 | 990 | 0.0115 | 1.0 |
| 0.0196 | 12.0 | 1080 | 0.0167 | 0.9955 |
| 0.0196 | 13.0 | 1170 | 0.0102 | 1.0 |
| 0.0196 | 14.0 | 1260 | 0.0093 | 1.0 |
| 0.0196 | 15.0 | 1350 | 0.0085 | 1.0 |
| 0.0196 | 16.0 | 1440 | 0.0079 | 1.0 |
| 0.0148 | 17.0 | 1530 | 0.0075 | 1.0 |
| 0.0148 | 18.0 | 1620 | 0.0074 | 1.0 |
| 0.0148 | 19.0 | 1710 | 0.0069 | 1.0 |
| 0.0148 | 20.0 | 1800 | 0.0065 | 1.0 |
| 0.0148 | 21.0 | 1890 | 0.0062 | 1.0 |
| 0.0148 | 22.0 | 1980 | 0.0062 | 1.0 |
| 0.0069 | 23.0 | 2070 | 0.0057 | 1.0 |
| 0.0069 | 24.0 | 2160 | 0.0055 | 1.0 |
| 0.0069 | 25.0 | 2250 | 0.0054 | 1.0 |
| 0.0069 | 26.0 | 2340 | 0.0053 | 1.0 |
| 0.0069 | 27.0 | 2430 | 0.0052 | 1.0 |
| 0.0055 | 28.0 | 2520 | 0.0051 | 1.0 |
| 0.0055 | 29.0 | 2610 | 0.0051 | 1.0 |
| 0.0055 | 30.0 | 2700 | 0.0051 | 1.0 |
Framework versions
- Transformers 4.38.1
- Pytorch 1.10.0+cu111
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024