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--- |
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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-in22k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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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-in22k-construction_type |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8804347826086957 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# swin-base-patch4-window7-224-in22k-construction_type |
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This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3095 |
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- Accuracy: 0.8804 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 7 |
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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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| 0.9839 | 0.9836 | 15 | 0.4599 | 0.8183 | |
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| 0.4167 | 1.9672 | 30 | 0.3605 | 0.8628 | |
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| 0.3853 | 2.9508 | 45 | 0.3272 | 0.8799 | |
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| 0.3302 | 4.0 | 61 | 0.3227 | 0.8763 | |
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| 0.3302 | 4.9836 | 76 | 0.3269 | 0.8753 | |
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| 0.3049 | 5.9672 | 91 | 0.3138 | 0.8799 | |
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| 0.2951 | 6.8852 | 105 | 0.3095 | 0.8804 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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