| --- |
| license: apache-2.0 |
| base_model: microsoft/swin-base-patch4-window7-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: swin-base-patch4-window7-224-MM_Classification_base |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8681177976952625 |
| --- |
| |
| <!-- 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-MM_Classification_base |
|
|
| This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3364 |
| - Accuracy: 0.8681 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 512 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.9771 | 1.0 | 19 | 0.5489 | 0.7913 | |
| | 0.4913 | 2.0 | 38 | 0.3562 | 0.8553 | |
| | 0.3633 | 3.0 | 57 | 0.3353 | 0.8668 | |
| | 0.3343 | 4.0 | 76 | 0.3177 | 0.8656 | |
| | 0.3096 | 5.0 | 95 | 0.3072 | 0.8758 | |
| | 0.2822 | 6.0 | 114 | 0.3213 | 0.8630 | |
| | 0.2749 | 7.0 | 133 | 0.3173 | 0.8643 | |
| | 0.2526 | 8.0 | 152 | 0.3110 | 0.8758 | |
| | 0.2405 | 9.0 | 171 | 0.3263 | 0.8758 | |
| | 0.2152 | 10.0 | 190 | 0.3268 | 0.8656 | |
| | 0.2226 | 11.0 | 209 | 0.3209 | 0.8732 | |
| | 0.2067 | 12.0 | 228 | 0.3289 | 0.8771 | |
| | 0.2019 | 13.0 | 247 | 0.3316 | 0.8745 | |
| | 0.195 | 14.0 | 266 | 0.3398 | 0.8732 | |
| | 0.1862 | 15.0 | 285 | 0.3364 | 0.8681 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.43.3 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
|
|
