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hushem_5x_deit_base_sgd_001_fold2

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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: facebook/deit-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_5x_deit_base_sgd_001_fold2
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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: 0.4888888888888889
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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_5x_deit_base_sgd_001_fold2
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+
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+ This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-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: 1.2313
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+ - Accuracy: 0.4889
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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: 0.001
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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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+ | 1.4159 | 1.0 | 27 | 1.4534 | 0.1333 |
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+ | 1.3715 | 2.0 | 54 | 1.4329 | 0.1333 |
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+ | 1.349 | 3.0 | 81 | 1.4161 | 0.1556 |
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+ | 1.3491 | 4.0 | 108 | 1.4025 | 0.1556 |
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+ | 1.3037 | 5.0 | 135 | 1.3915 | 0.2 |
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+ | 1.2977 | 6.0 | 162 | 1.3813 | 0.2444 |
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+ | 1.2881 | 7.0 | 189 | 1.3728 | 0.2889 |
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+ | 1.2735 | 8.0 | 216 | 1.3643 | 0.3333 |
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+ | 1.2461 | 9.0 | 243 | 1.3568 | 0.3556 |
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+ | 1.2282 | 10.0 | 270 | 1.3495 | 0.3556 |
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+ | 1.2197 | 11.0 | 297 | 1.3426 | 0.3556 |
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+ | 1.1815 | 12.0 | 324 | 1.3361 | 0.3778 |
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+ | 1.1874 | 13.0 | 351 | 1.3296 | 0.3778 |
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+ | 1.1512 | 14.0 | 378 | 1.3234 | 0.3778 |
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+ | 1.169 | 15.0 | 405 | 1.3177 | 0.4 |
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+ | 1.1635 | 16.0 | 432 | 1.3122 | 0.4 |
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+ | 1.1212 | 17.0 | 459 | 1.3068 | 0.4 |
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+ | 1.1132 | 18.0 | 486 | 1.3013 | 0.4 |
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+ | 1.0934 | 19.0 | 513 | 1.2960 | 0.4 |
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+ | 1.0783 | 20.0 | 540 | 1.2914 | 0.4 |
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+ | 1.0674 | 21.0 | 567 | 1.2869 | 0.4 |
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+ | 1.0564 | 22.0 | 594 | 1.2826 | 0.4222 |
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+ | 1.0602 | 23.0 | 621 | 1.2784 | 0.4444 |
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+ | 1.0292 | 24.0 | 648 | 1.2744 | 0.4667 |
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+ | 1.0348 | 25.0 | 675 | 1.2706 | 0.4667 |
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+ | 1.0373 | 26.0 | 702 | 1.2671 | 0.4667 |
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+ | 1.0143 | 27.0 | 729 | 1.2638 | 0.4667 |
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+ | 1.0044 | 28.0 | 756 | 1.2607 | 0.4667 |
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+ | 0.9861 | 29.0 | 783 | 1.2578 | 0.4667 |
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+ | 1.0112 | 30.0 | 810 | 1.2551 | 0.4667 |
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+ | 0.9561 | 31.0 | 837 | 1.2525 | 0.4667 |
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+ | 0.9839 | 32.0 | 864 | 1.2500 | 0.4667 |
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+ | 0.9768 | 33.0 | 891 | 1.2477 | 0.4667 |
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+ | 0.936 | 34.0 | 918 | 1.2456 | 0.4667 |
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+ | 0.9571 | 35.0 | 945 | 1.2436 | 0.4667 |
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+ | 0.9423 | 36.0 | 972 | 1.2418 | 0.4667 |
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+ | 0.9413 | 37.0 | 999 | 1.2401 | 0.4667 |
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+ | 0.9304 | 38.0 | 1026 | 1.2386 | 0.4889 |
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+ | 0.9391 | 39.0 | 1053 | 1.2372 | 0.4889 |
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+ | 0.9013 | 40.0 | 1080 | 1.2360 | 0.4889 |
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+ | 0.9198 | 41.0 | 1107 | 1.2349 | 0.4889 |
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+ | 0.9119 | 42.0 | 1134 | 1.2340 | 0.4889 |
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+ | 0.9214 | 43.0 | 1161 | 1.2332 | 0.4889 |
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+ | 0.8928 | 44.0 | 1188 | 1.2325 | 0.4889 |
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+ | 0.9196 | 45.0 | 1215 | 1.2320 | 0.4889 |
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+ | 0.906 | 46.0 | 1242 | 1.2316 | 0.4889 |
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+ | 0.9098 | 47.0 | 1269 | 1.2314 | 0.4889 |
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+ | 0.9113 | 48.0 | 1296 | 1.2313 | 0.4889 |
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+ | 0.9534 | 49.0 | 1323 | 1.2313 | 0.4889 |
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+ | 0.8999 | 50.0 | 1350 | 1.2313 | 0.4889 |
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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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