| ---
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| library_name: transformers
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| license: apache-2.0
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| base_model: microsoft/swin-base-patch4-window7-224
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| tags:
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| - generated_from_trainer
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| metrics:
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| - accuracy
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| model-index:
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| - name: swin-base-patch4-window7-224_11092024
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| results: []
|
| ---
|
|
|
| <!-- 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. -->
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|
|
| # swin-base-patch4-window7-224_11092024
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|
|
| This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.5135
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| - Accuracy: 0.8337
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|
|
| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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| More information needed
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|
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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|
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| ### Training hyperparameters
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| The following hyperparameters were used during training:
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| - learning_rate: 0.0003
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| - train_batch_size: 16
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| - eval_batch_size: 8
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| - seed: 42
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| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| - lr_scheduler_type: linear
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| - num_epochs: 20
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|
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| ### Training results
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|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| |:-------------:|:-----:|:----:|:---------------:|:--------:|
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| | 1.0366 | 1.0 | 400 | 0.9471 | 0.72 |
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| | 0.8257 | 2.0 | 800 | 0.7889 | 0.7538 |
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| | 0.7119 | 3.0 | 1200 | 0.7232 | 0.7775 |
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| | 0.6969 | 4.0 | 1600 | 0.6739 | 0.7837 |
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| | 0.6487 | 5.0 | 2000 | 0.6371 | 0.7863 |
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| | 0.5956 | 6.0 | 2400 | 0.6198 | 0.7887 |
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| | 0.5604 | 7.0 | 2800 | 0.5941 | 0.8025 |
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| | 0.5732 | 8.0 | 3200 | 0.5867 | 0.795 |
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| | 0.5578 | 9.0 | 3600 | 0.5705 | 0.8025 |
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| | 0.5449 | 10.0 | 4000 | 0.5575 | 0.8113 |
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| | 0.5419 | 11.0 | 4400 | 0.5505 | 0.8213 |
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| | 0.5086 | 12.0 | 4800 | 0.5385 | 0.8213 |
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| | 0.4929 | 13.0 | 5200 | 0.5340 | 0.8213 |
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| | 0.4701 | 14.0 | 5600 | 0.5297 | 0.8187 |
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| | 0.4803 | 15.0 | 6000 | 0.5240 | 0.8225 |
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| | 0.4988 | 16.0 | 6400 | 0.5197 | 0.83 |
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| | 0.4842 | 17.0 | 6800 | 0.5165 | 0.8313 |
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| | 0.4917 | 18.0 | 7200 | 0.5148 | 0.8313 |
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| | 0.4734 | 19.0 | 7600 | 0.5140 | 0.8325 |
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| | 0.4714 | 20.0 | 8000 | 0.5135 | 0.8337 |
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| ### Framework versions
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|
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| - Transformers 4.45.2
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| - Pytorch 2.4.1+cpu
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| - Datasets 3.0.1
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| - Tokenizers 0.20.1
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| |
