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vit-finetuned-1
DeepTrader/vit-finetuned-1
vit-finetuned-1 is a image classification model from DeepTrader. 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
- Nov 3, 2024
- Updated
- Nov 3, 2024
- SHA
- bff00c9b
Base models
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-finetuned-1
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2750
- Accuracy: 0.5
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 0.1575 | 1.0 |
| No log | 2.0 | 2 | 0.1166 | 1.0 |
| No log | 3.0 | 3 | 0.2496 | 1.0 |
| No log | 4.0 | 4 | 0.4093 | 0.5 |
| No log | 5.0 | 5 | 0.6732 | 0.5 |
| No log | 6.0 | 6 | 0.9200 | 0.5 |
| No log | 7.0 | 7 | 1.0925 | 0.5 |
| No log | 8.0 | 8 | 1.1963 | 0.5 |
| No log | 9.0 | 9 | 1.2521 | 0.5 |
| No log | 10.0 | 10 | 1.2750 | 0.5 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cpu
- Datasets 3.1.0
- Tokenizers 0.20.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 3, 2024
- Updated
- Nov 3, 2024