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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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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-tiny-patch4-window7-224-finetuned-sealv1 |
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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: 0.946969696969697 |
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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-tiny-patch4-window7-224-finetuned-sealv1 |
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4069 |
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- Accuracy: 0.9470 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 30 |
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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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| No log | 0.95 | 9 | 1.1667 | 0.6023 | |
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| 1.2777 | 2.0 | 19 | 0.9542 | 0.8864 | |
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| 0.8743 | 2.95 | 28 | 0.5694 | 0.9015 | |
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| 0.5282 | 4.0 | 38 | 0.3682 | 0.9129 | |
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| 0.2988 | 4.95 | 47 | 0.2135 | 0.9545 | |
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| 0.1832 | 6.0 | 57 | 0.2820 | 0.9167 | |
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| 0.1867 | 6.95 | 66 | 0.1944 | 0.9432 | |
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| 0.1077 | 8.0 | 76 | 0.2345 | 0.9432 | |
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| 0.0571 | 8.95 | 85 | 0.2389 | 0.9470 | |
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| 0.0379 | 10.0 | 95 | 0.2260 | 0.9432 | |
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| 0.0233 | 10.95 | 104 | 0.2329 | 0.9432 | |
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| 0.0163 | 12.0 | 114 | 0.2610 | 0.9356 | |
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| 0.019 | 12.95 | 123 | 0.3660 | 0.9508 | |
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| 0.0113 | 14.0 | 133 | 0.2777 | 0.9470 | |
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| 0.0084 | 14.95 | 142 | 0.3123 | 0.9508 | |
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| 0.008 | 16.0 | 152 | 0.3222 | 0.9470 | |
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| 0.0048 | 16.95 | 161 | 0.3232 | 0.9470 | |
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| 0.0075 | 18.0 | 171 | 0.3476 | 0.9508 | |
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| 0.0048 | 18.95 | 180 | 0.3304 | 0.9470 | |
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| 0.0143 | 20.0 | 190 | 0.4560 | 0.9432 | |
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| 0.0143 | 20.95 | 199 | 0.3720 | 0.9432 | |
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| 0.0019 | 22.0 | 209 | 0.3579 | 0.9394 | |
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| 0.0063 | 22.95 | 218 | 0.4064 | 0.9432 | |
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| 0.0023 | 24.0 | 228 | 0.4741 | 0.9394 | |
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| 0.0015 | 24.95 | 237 | 0.4111 | 0.9470 | |
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| 0.0022 | 26.0 | 247 | 0.3914 | 0.9432 | |
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| 0.0008 | 26.95 | 256 | 0.3945 | 0.9432 | |
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| 0.0024 | 28.0 | 266 | 0.4053 | 0.9470 | |
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| 0.0026 | 28.42 | 270 | 0.4069 | 0.9470 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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