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hushem_1x_beit_base_adamax_00001_fold4

Image Classification
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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: hushem_1x_beit_base_adamax_00001_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: test
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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: 0.8571428571428571
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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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+ # hushem_1x_beit_base_adamax_00001_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: 0.3525
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+ - Accuracy: 0.8571
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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: 1e-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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+ - 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: 50
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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 | 1.0 | 6 | 1.2487 | 0.4524 |
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+ | 1.3325 | 2.0 | 12 | 1.1186 | 0.5476 |
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+ | 1.3325 | 3.0 | 18 | 1.0007 | 0.6429 |
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+ | 0.9723 | 4.0 | 24 | 0.9193 | 0.6429 |
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+ | 0.7474 | 5.0 | 30 | 0.8604 | 0.6429 |
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+ | 0.7474 | 6.0 | 36 | 0.7650 | 0.7143 |
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+ | 0.5775 | 7.0 | 42 | 0.6832 | 0.7619 |
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+ | 0.5775 | 8.0 | 48 | 0.6554 | 0.7381 |
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+ | 0.4415 | 9.0 | 54 | 0.6117 | 0.7381 |
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+ | 0.3035 | 10.0 | 60 | 0.5783 | 0.7857 |
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+ | 0.3035 | 11.0 | 66 | 0.5572 | 0.7857 |
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+ | 0.2259 | 12.0 | 72 | 0.5149 | 0.8095 |
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+ | 0.2259 | 13.0 | 78 | 0.4887 | 0.8571 |
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+ | 0.1918 | 14.0 | 84 | 0.4779 | 0.8095 |
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+ | 0.1546 | 15.0 | 90 | 0.4660 | 0.8095 |
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+ | 0.1546 | 16.0 | 96 | 0.4640 | 0.8333 |
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+ | 0.1177 | 17.0 | 102 | 0.4361 | 0.9048 |
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+ | 0.1177 | 18.0 | 108 | 0.4152 | 0.8810 |
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+ | 0.1109 | 19.0 | 114 | 0.4213 | 0.9048 |
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+ | 0.0885 | 20.0 | 120 | 0.4055 | 0.9048 |
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+ | 0.0885 | 21.0 | 126 | 0.3889 | 0.8810 |
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+ | 0.0665 | 22.0 | 132 | 0.3826 | 0.8810 |
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+ | 0.0665 | 23.0 | 138 | 0.3817 | 0.9048 |
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+ | 0.0682 | 24.0 | 144 | 0.3714 | 0.9048 |
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+ | 0.055 | 25.0 | 150 | 0.3759 | 0.8810 |
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+ | 0.055 | 26.0 | 156 | 0.3597 | 0.9048 |
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+ | 0.0545 | 27.0 | 162 | 0.3543 | 0.9048 |
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+ | 0.0545 | 28.0 | 168 | 0.3635 | 0.8810 |
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+ | 0.0561 | 29.0 | 174 | 0.3559 | 0.8810 |
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+ | 0.0403 | 30.0 | 180 | 0.3405 | 0.9048 |
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+ | 0.0403 | 31.0 | 186 | 0.3424 | 0.9048 |
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+ | 0.048 | 32.0 | 192 | 0.3445 | 0.8810 |
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+ | 0.048 | 33.0 | 198 | 0.3419 | 0.8810 |
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+ | 0.0375 | 34.0 | 204 | 0.3424 | 0.8810 |
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+ | 0.0438 | 35.0 | 210 | 0.3440 | 0.8810 |
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+ | 0.0438 | 36.0 | 216 | 0.3465 | 0.8571 |
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+ | 0.0357 | 37.0 | 222 | 0.3469 | 0.8571 |
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+ | 0.0357 | 38.0 | 228 | 0.3472 | 0.8571 |
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+ | 0.0346 | 39.0 | 234 | 0.3498 | 0.8571 |
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+ | 0.0356 | 40.0 | 240 | 0.3512 | 0.8571 |
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+ | 0.0356 | 41.0 | 246 | 0.3523 | 0.8571 |
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+ | 0.042 | 42.0 | 252 | 0.3525 | 0.8571 |
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+ | 0.042 | 43.0 | 258 | 0.3525 | 0.8571 |
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+ | 0.033 | 44.0 | 264 | 0.3525 | 0.8571 |
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+ | 0.0336 | 45.0 | 270 | 0.3525 | 0.8571 |
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+ | 0.0336 | 46.0 | 276 | 0.3525 | 0.8571 |
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+ | 0.0414 | 47.0 | 282 | 0.3525 | 0.8571 |
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+ | 0.0414 | 48.0 | 288 | 0.3525 | 0.8571 |
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+ | 0.0414 | 49.0 | 294 | 0.3525 | 0.8571 |
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+ | 0.0317 | 50.0 | 300 | 0.3525 | 0.8571 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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