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README.md ADDED
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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-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-papsmear
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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: train
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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: 0.8897058823529411
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+ ---
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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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+
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+ # swin-tiny-patch4-window7-224-finetuned-papsmear
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+
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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: 0.2026
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+ - Accuracy: 0.8897
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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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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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 1.4844 | 0.9935 | 38 | 1.4298 | 0.4118 |
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+ | 0.8905 | 1.9869 | 76 | 0.8110 | 0.6544 |
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+ | 0.9097 | 2.9804 | 114 | 0.7109 | 0.7132 |
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+ | 0.6238 | 4.0 | 153 | 0.9197 | 0.6544 |
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+ | 0.4456 | 4.9935 | 191 | 0.4652 | 0.8015 |
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+ | 0.4394 | 5.9869 | 229 | 0.5188 | 0.8015 |
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+ | 0.3156 | 6.9804 | 267 | 0.3447 | 0.8529 |
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+ | 0.2212 | 8.0 | 306 | 0.3509 | 0.8382 |
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+ | 0.2402 | 8.9935 | 344 | 0.3939 | 0.8235 |
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+ | 0.1733 | 9.9869 | 382 | 0.2444 | 0.8897 |
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+ | 0.1953 | 10.9804 | 420 | 0.2639 | 0.8676 |
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+ | 0.1363 | 12.0 | 459 | 0.2645 | 0.8824 |
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+ | 0.1234 | 12.9935 | 497 | 0.2027 | 0.9044 |
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+ | 0.1282 | 13.9869 | 535 | 0.2027 | 0.9044 |
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+ | 0.1036 | 14.9020 | 570 | 0.2026 | 0.8897 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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