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BilalMuftuoglu
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beit-base-patch16-224-hasta-65-fold5

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  2. model.safetensors +1 -1
  3. runs/May23_14-21-45_2bc4f829fe52/events.out.tfevents.1716474106.2bc4f829fe52.989.18 +2 -2
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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-fold5
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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: 0.5277777777777778
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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-fold5
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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: 1.0692
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+ - Accuracy: 0.5278
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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 | 1.1680 | 0.3333 |
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+ | No log | 1.7143 | 3 | 1.2100 | 0.1944 |
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+ | No log | 2.8571 | 5 | 1.3667 | 0.2778 |
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+ | No log | 4.0 | 7 | 1.1208 | 0.3889 |
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+ | No log | 4.5714 | 8 | 1.1168 | 0.3611 |
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+ | 1.132 | 5.7143 | 10 | 1.4031 | 0.2778 |
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+ | 1.132 | 6.8571 | 12 | 1.2012 | 0.3333 |
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+ | 1.132 | 8.0 | 14 | 1.2353 | 0.2778 |
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+ | 1.132 | 8.5714 | 15 | 1.2099 | 0.3056 |
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+ | 1.132 | 9.7143 | 17 | 1.0942 | 0.3611 |
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+ | 1.132 | 10.8571 | 19 | 1.1301 | 0.4444 |
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+ | 1.0271 | 12.0 | 21 | 1.0591 | 0.4167 |
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+ | 1.0271 | 12.5714 | 22 | 1.0648 | 0.4444 |
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+ | 1.0271 | 13.7143 | 24 | 1.1125 | 0.4722 |
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+ | 1.0271 | 14.8571 | 26 | 1.1097 | 0.4722 |
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+ | 1.0271 | 16.0 | 28 | 1.0616 | 0.4444 |
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+ | 1.0271 | 16.5714 | 29 | 1.0284 | 0.4722 |
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+ | 0.9507 | 17.7143 | 31 | 1.0291 | 0.5 |
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+ | 0.9507 | 18.8571 | 33 | 1.0692 | 0.4722 |
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+ | 0.9507 | 20.0 | 35 | 1.1153 | 0.5 |
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+ | 0.9507 | 20.5714 | 36 | 1.1719 | 0.4444 |
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+ | 0.9507 | 21.7143 | 38 | 1.0161 | 0.4444 |
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+ | 0.8001 | 22.8571 | 40 | 1.1361 | 0.4444 |
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+ | 0.8001 | 24.0 | 42 | 1.3277 | 0.4444 |
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+ | 0.8001 | 24.5714 | 43 | 1.1331 | 0.5 |
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+ | 0.8001 | 25.7143 | 45 | 1.0659 | 0.4722 |
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+ | 0.8001 | 26.8571 | 47 | 1.1309 | 0.5278 |
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+ | 0.8001 | 28.0 | 49 | 1.1241 | 0.5556 |
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+ | 0.7175 | 28.5714 | 50 | 1.1371 | 0.5278 |
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+ | 0.7175 | 29.7143 | 52 | 1.0928 | 0.5 |
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+ | 0.7175 | 30.8571 | 54 | 1.2129 | 0.4444 |
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+ | 0.7175 | 32.0 | 56 | 1.0321 | 0.5 |
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+ | 0.7175 | 32.5714 | 57 | 1.0809 | 0.5278 |
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+ | 0.7175 | 33.7143 | 59 | 0.9813 | 0.5278 |
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+ | 0.6766 | 34.8571 | 61 | 1.0617 | 0.5 |
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+ | 0.6766 | 36.0 | 63 | 0.9618 | 0.5278 |
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+ | 0.6766 | 36.5714 | 64 | 0.9541 | 0.5556 |
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+ | 0.6766 | 37.7143 | 66 | 0.9689 | 0.5278 |
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+ | 0.6766 | 38.8571 | 68 | 1.1063 | 0.5556 |
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+ | 0.5934 | 40.0 | 70 | 1.0139 | 0.5 |
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+ | 0.5934 | 40.5714 | 71 | 1.0087 | 0.5 |
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+ | 0.5934 | 41.7143 | 73 | 1.0309 | 0.5 |
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+ | 0.5934 | 42.8571 | 75 | 1.0636 | 0.5 |
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+ | 0.5934 | 44.0 | 77 | 1.1057 | 0.5 |
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+ | 0.5934 | 44.5714 | 78 | 1.1015 | 0.4722 |
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+ | 0.4926 | 45.7143 | 80 | 1.0938 | 0.5278 |
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+ | 0.4926 | 46.8571 | 82 | 1.0807 | 0.5 |
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+ | 0.4926 | 48.0 | 84 | 1.1275 | 0.5278 |
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+ | 0.4926 | 48.5714 | 85 | 1.1604 | 0.5278 |
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+ | 0.4926 | 49.7143 | 87 | 1.1296 | 0.5278 |
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+ | 0.4926 | 50.8571 | 89 | 1.0748 | 0.5278 |
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+ | 0.4964 | 52.0 | 91 | 1.0716 | 0.5278 |
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+ | 0.4964 | 52.5714 | 92 | 1.0780 | 0.5278 |
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+ | 0.4964 | 53.7143 | 94 | 1.0755 | 0.5278 |
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+ | 0.4964 | 54.8571 | 96 | 1.0680 | 0.5278 |
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+ | 0.4964 | 56.0 | 98 | 1.0676 | 0.5278 |
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+ | 0.4964 | 56.5714 | 99 | 1.0692 | 0.5278 |
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+ | 0.404 | 57.1429 | 100 | 1.0692 | 0.5278 |
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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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