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BilalMuftuoglu
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beit-base-patch16-224-hasta-65-fold1

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  2. model.safetensors +1 -1
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README.md ADDED
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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-65-fold1
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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: 0.5833333333333334
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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-65-fold1
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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: 0.9102
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+ - Accuracy: 0.5833
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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 | 1.1951 | 0.3333 |
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+ | No log | 1.7143 | 3 | 1.2409 | 0.3056 |
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+ | No log | 2.8571 | 5 | 1.2181 | 0.3056 |
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+ | No log | 4.0 | 7 | 1.1308 | 0.5 |
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+ | No log | 4.5714 | 8 | 1.1858 | 0.5278 |
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+ | 1.092 | 5.7143 | 10 | 1.2798 | 0.3056 |
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+ | 1.092 | 6.8571 | 12 | 1.0892 | 0.3611 |
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+ | 1.092 | 8.0 | 14 | 1.2658 | 0.3889 |
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+ | 1.092 | 8.5714 | 15 | 1.1603 | 0.5 |
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+ | 1.092 | 9.7143 | 17 | 1.0786 | 0.4167 |
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+ | 1.092 | 10.8571 | 19 | 1.2400 | 0.4167 |
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+ | 0.9727 | 12.0 | 21 | 1.2929 | 0.3889 |
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+ | 0.9727 | 12.5714 | 22 | 1.1613 | 0.3889 |
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+ | 0.9727 | 13.7143 | 24 | 0.9838 | 0.6111 |
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+ | 0.9727 | 14.8571 | 26 | 1.2316 | 0.3889 |
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+ | 0.9727 | 16.0 | 28 | 1.1520 | 0.4722 |
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+ | 0.9727 | 16.5714 | 29 | 1.0345 | 0.5556 |
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+ | 0.8844 | 17.7143 | 31 | 1.0000 | 0.5 |
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+ | 0.8844 | 18.8571 | 33 | 0.9933 | 0.5278 |
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+ | 0.8844 | 20.0 | 35 | 1.0512 | 0.5556 |
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+ | 0.8844 | 20.5714 | 36 | 0.9950 | 0.5556 |
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+ | 0.8844 | 21.7143 | 38 | 0.9621 | 0.4722 |
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+ | 0.7447 | 22.8571 | 40 | 0.8812 | 0.5278 |
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+ | 0.7447 | 24.0 | 42 | 1.0244 | 0.5833 |
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+ | 0.7447 | 24.5714 | 43 | 1.0124 | 0.5833 |
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+ | 0.7447 | 25.7143 | 45 | 0.8908 | 0.6389 |
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+ | 0.7447 | 26.8571 | 47 | 0.8185 | 0.5833 |
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+ | 0.7447 | 28.0 | 49 | 0.9409 | 0.5556 |
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+ | 0.6176 | 28.5714 | 50 | 1.0401 | 0.5556 |
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+ | 0.6176 | 29.7143 | 52 | 1.0989 | 0.5556 |
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+ | 0.6176 | 30.8571 | 54 | 0.9102 | 0.5833 |
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+ | 0.6176 | 32.0 | 56 | 0.8855 | 0.5833 |
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+ | 0.6176 | 32.5714 | 57 | 0.8974 | 0.5556 |
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+ | 0.6176 | 33.7143 | 59 | 0.9419 | 0.6111 |
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+ | 0.4929 | 34.8571 | 61 | 0.9471 | 0.5833 |
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+ | 0.4929 | 36.0 | 63 | 0.8609 | 0.5833 |
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+ | 0.4929 | 36.5714 | 64 | 0.8558 | 0.5833 |
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+ | 0.4929 | 37.7143 | 66 | 0.8449 | 0.5556 |
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+ | 0.4929 | 38.8571 | 68 | 0.8136 | 0.6667 |
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+ | 0.463 | 40.0 | 70 | 0.8281 | 0.6944 |
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+ | 0.463 | 40.5714 | 71 | 0.8227 | 0.6944 |
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+ | 0.463 | 41.7143 | 73 | 0.8323 | 0.5833 |
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+ | 0.463 | 42.8571 | 75 | 0.8436 | 0.5833 |
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+ | 0.463 | 44.0 | 77 | 0.8390 | 0.5833 |
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+ | 0.463 | 44.5714 | 78 | 0.8580 | 0.6111 |
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+ | 0.3995 | 45.7143 | 80 | 0.9375 | 0.6111 |
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+ | 0.3995 | 46.8571 | 82 | 0.9897 | 0.5556 |
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+ | 0.3995 | 48.0 | 84 | 0.9785 | 0.5556 |
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+ | 0.3995 | 48.5714 | 85 | 0.9336 | 0.6389 |
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+ | 0.3995 | 49.7143 | 87 | 0.8504 | 0.6389 |
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+ | 0.3995 | 50.8571 | 89 | 0.8450 | 0.6667 |
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+ | 0.3697 | 52.0 | 91 | 0.8531 | 0.6389 |
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+ | 0.3697 | 52.5714 | 92 | 0.8728 | 0.6389 |
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+ | 0.3697 | 53.7143 | 94 | 0.9076 | 0.6667 |
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+ | 0.3697 | 54.8571 | 96 | 0.9175 | 0.6389 |
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+ | 0.3697 | 56.0 | 98 | 0.9145 | 0.5833 |
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+ | 0.3697 | 56.5714 | 99 | 0.9119 | 0.5833 |
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+ | 0.3259 | 57.1429 | 100 | 0.9102 | 0.5833 |
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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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