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swin-base-patch4-window7-224-finetuned-lora-scenes
elidandar/swin-base-patch4-window7-224-finetuned-lora-scenes
swin-base-patch4-window7-224-finetuned-lora-scenes is a machine learning model from elidandar. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Updated Dec 6, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Dec 6, 2023
- Updated
- Dec 6, 2023
- SHA
- eaf9692a
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. -->
swin-base-patch4-window7-224-finetuned-lora-scenes
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0407
- Accuracy: 0.9853
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: 0.005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2038 | 0.97 | 27 | 0.0655 | 0.9763 |
| 0.1143 | 1.98 | 55 | 0.0557 | 0.9820 |
| 0.1224 | 2.99 | 83 | 0.0517 | 0.9763 |
| 0.0891 | 4.0 | 111 | 0.0439 | 0.9831 |
| 0.0696 | 4.97 | 138 | 0.0407 | 0.9853 |
| 0.0716 | 5.84 | 162 | 0.0436 | 0.9853 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Dec 6, 2023
- Updated
- Dec 6, 2023