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BilalMuftuoglu
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beit-base-patch16-224-hasta-55-fold4

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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224
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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: beit-base-patch16-224-hasta-55-fold4
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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: 0.6666666666666666
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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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+ # beit-base-patch16-224-hasta-55-fold4
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1951
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+ - Accuracy: 0.6667
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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: 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: 100
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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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+ | No log | 0.5714 | 1 | 1.2503 | 0.4444 |
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+ | No log | 1.7143 | 3 | 1.1731 | 0.4167 |
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+ | No log | 2.8571 | 5 | 1.0852 | 0.5278 |
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+ | No log | 4.0 | 7 | 1.0787 | 0.5 |
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+ | No log | 4.5714 | 8 | 1.1199 | 0.5278 |
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+ | 1.0532 | 5.7143 | 10 | 1.0584 | 0.4722 |
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+ | 1.0532 | 6.8571 | 12 | 1.0800 | 0.5278 |
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+ | 1.0532 | 8.0 | 14 | 1.1635 | 0.4722 |
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+ | 1.0532 | 8.5714 | 15 | 1.1171 | 0.4444 |
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+ | 1.0532 | 9.7143 | 17 | 1.5254 | 0.3889 |
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+ | 1.0532 | 10.8571 | 19 | 1.1236 | 0.4444 |
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+ | 0.9087 | 12.0 | 21 | 1.0255 | 0.5556 |
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+ | 0.9087 | 12.5714 | 22 | 1.1108 | 0.5278 |
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+ | 0.9087 | 13.7143 | 24 | 1.0365 | 0.5278 |
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+ | 0.9087 | 14.8571 | 26 | 1.0638 | 0.5 |
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+ | 0.9087 | 16.0 | 28 | 1.1090 | 0.6111 |
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+ | 0.9087 | 16.5714 | 29 | 1.1166 | 0.5556 |
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+ | 0.7925 | 17.7143 | 31 | 1.0650 | 0.4722 |
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+ | 0.7925 | 18.8571 | 33 | 1.3085 | 0.5556 |
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+ | 0.7925 | 20.0 | 35 | 1.1624 | 0.5278 |
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+ | 0.7925 | 20.5714 | 36 | 0.9994 | 0.5556 |
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+ | 0.7925 | 21.7143 | 38 | 1.1054 | 0.4722 |
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+ | 0.7472 | 22.8571 | 40 | 1.0926 | 0.5833 |
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+ | 0.7472 | 24.0 | 42 | 1.1054 | 0.6111 |
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+ | 0.7472 | 24.5714 | 43 | 1.0486 | 0.5556 |
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+ | 0.7472 | 25.7143 | 45 | 1.0454 | 0.5556 |
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+ | 0.7472 | 26.8571 | 47 | 1.0267 | 0.6389 |
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+ | 0.7472 | 28.0 | 49 | 1.0684 | 0.6667 |
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+ | 0.572 | 28.5714 | 50 | 1.0575 | 0.6111 |
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+ | 0.572 | 29.7143 | 52 | 1.1591 | 0.5833 |
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+ | 0.572 | 30.8571 | 54 | 1.1837 | 0.5833 |
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+ | 0.572 | 32.0 | 56 | 1.0444 | 0.6667 |
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+ | 0.572 | 32.5714 | 57 | 1.0450 | 0.6667 |
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+ | 0.572 | 33.7143 | 59 | 1.0975 | 0.6667 |
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+ | 0.471 | 34.8571 | 61 | 1.1131 | 0.6667 |
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+ | 0.471 | 36.0 | 63 | 1.1204 | 0.5833 |
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+ | 0.471 | 36.5714 | 64 | 1.0992 | 0.5833 |
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+ | 0.471 | 37.7143 | 66 | 1.0879 | 0.6389 |
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+ | 0.471 | 38.8571 | 68 | 1.0981 | 0.6111 |
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+ | 0.3896 | 40.0 | 70 | 1.0576 | 0.6667 |
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+ | 0.3896 | 40.5714 | 71 | 1.0612 | 0.6389 |
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+ | 0.3896 | 41.7143 | 73 | 1.1195 | 0.6667 |
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+ | 0.3896 | 42.8571 | 75 | 1.1974 | 0.6667 |
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+ | 0.3896 | 44.0 | 77 | 1.1353 | 0.6667 |
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+ | 0.3896 | 44.5714 | 78 | 1.1143 | 0.6667 |
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+ | 0.3775 | 45.7143 | 80 | 1.1055 | 0.6667 |
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+ | 0.3775 | 46.8571 | 82 | 1.1997 | 0.6667 |
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+ | 0.3775 | 48.0 | 84 | 1.3267 | 0.6667 |
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+ | 0.3775 | 48.5714 | 85 | 1.3027 | 0.6667 |
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+ | 0.3775 | 49.7143 | 87 | 1.1593 | 0.7222 |
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+ | 0.3775 | 50.8571 | 89 | 1.0970 | 0.6111 |
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+ | 0.3623 | 52.0 | 91 | 1.0902 | 0.6111 |
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+ | 0.3623 | 52.5714 | 92 | 1.0908 | 0.6111 |
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+ | 0.3623 | 53.7143 | 94 | 1.1214 | 0.6389 |
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+ | 0.3623 | 54.8571 | 96 | 1.1691 | 0.6944 |
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+ | 0.3623 | 56.0 | 98 | 1.1914 | 0.6667 |
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+ | 0.3623 | 56.5714 | 99 | 1.1949 | 0.6667 |
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+ | 0.3455 | 57.1429 | 100 | 1.1951 | 0.6667 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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