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hushem_5x_beit_base_adamax_001_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: hushem_5x_beit_base_adamax_001_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: 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: 0.4444444444444444
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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_beit_base_adamax_001_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: 6.2787
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+ - Accuracy: 0.4444
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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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+ | 1.4418 | 1.0 | 27 | 1.4079 | 0.2444 |
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+ | 1.2606 | 2.0 | 54 | 1.4566 | 0.4 |
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+ | 1.1141 | 3.0 | 81 | 1.4147 | 0.3111 |
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+ | 0.9738 | 4.0 | 108 | 1.7371 | 0.3556 |
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+ | 0.7887 | 5.0 | 135 | 1.5516 | 0.3778 |
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+ | 0.7198 | 6.0 | 162 | 1.3626 | 0.4 |
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+ | 0.8269 | 7.0 | 189 | 1.5448 | 0.3778 |
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+ | 0.8171 | 8.0 | 216 | 1.4576 | 0.4 |
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+ | 0.7255 | 9.0 | 243 | 2.3915 | 0.3778 |
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+ | 0.6369 | 10.0 | 270 | 1.6627 | 0.3778 |
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+ | 0.6809 | 11.0 | 297 | 1.5201 | 0.3556 |
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+ | 0.6237 | 12.0 | 324 | 1.3289 | 0.4222 |
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+ | 0.6768 | 13.0 | 351 | 1.6115 | 0.3556 |
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+ | 0.6336 | 14.0 | 378 | 2.0397 | 0.3778 |
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+ | 0.5238 | 15.0 | 405 | 1.5857 | 0.3778 |
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+ | 0.5016 | 16.0 | 432 | 1.4047 | 0.4444 |
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+ | 0.4321 | 17.0 | 459 | 2.2039 | 0.3556 |
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+ | 0.4791 | 18.0 | 486 | 2.3823 | 0.3778 |
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+ | 0.484 | 19.0 | 513 | 1.4706 | 0.4222 |
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+ | 0.4812 | 20.0 | 540 | 1.6485 | 0.4222 |
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+ | 0.4413 | 21.0 | 567 | 1.7092 | 0.4 |
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+ | 0.4306 | 22.0 | 594 | 1.8582 | 0.4 |
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+ | 0.37 | 23.0 | 621 | 1.8653 | 0.3778 |
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+ | 0.3048 | 24.0 | 648 | 1.6342 | 0.4444 |
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+ | 0.3515 | 25.0 | 675 | 1.5211 | 0.4889 |
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+ | 0.3558 | 26.0 | 702 | 1.9714 | 0.4222 |
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+ | 0.2599 | 27.0 | 729 | 1.7243 | 0.4667 |
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+ | 0.267 | 28.0 | 756 | 1.7049 | 0.5111 |
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+ | 0.2625 | 29.0 | 783 | 2.1704 | 0.4222 |
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+ | 0.2368 | 30.0 | 810 | 2.2942 | 0.4667 |
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+ | 0.2036 | 31.0 | 837 | 2.0691 | 0.4667 |
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+ | 0.1938 | 32.0 | 864 | 2.7340 | 0.4 |
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+ | 0.1597 | 33.0 | 891 | 3.0661 | 0.4 |
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+ | 0.1166 | 34.0 | 918 | 2.8536 | 0.4667 |
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+ | 0.1248 | 35.0 | 945 | 2.9508 | 0.4444 |
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+ | 0.121 | 36.0 | 972 | 3.2153 | 0.4667 |
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+ | 0.0801 | 37.0 | 999 | 3.0021 | 0.4222 |
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+ | 0.0529 | 38.0 | 1026 | 3.3247 | 0.4222 |
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+ | 0.0434 | 39.0 | 1053 | 4.0394 | 0.4667 |
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+ | 0.0599 | 40.0 | 1080 | 4.1062 | 0.4889 |
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+ | 0.0437 | 41.0 | 1107 | 5.3485 | 0.4667 |
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+ | 0.0045 | 42.0 | 1134 | 5.3122 | 0.4667 |
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+ | 0.0368 | 43.0 | 1161 | 5.1937 | 0.4667 |
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+ | 0.0032 | 44.0 | 1188 | 5.6803 | 0.4889 |
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+ | 0.0061 | 45.0 | 1215 | 5.8620 | 0.4444 |
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+ | 0.0035 | 46.0 | 1242 | 5.9016 | 0.4889 |
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+ | 0.0011 | 47.0 | 1269 | 6.3136 | 0.4444 |
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+ | 0.0277 | 48.0 | 1296 | 6.2816 | 0.4444 |
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+ | 0.0067 | 49.0 | 1323 | 6.2787 | 0.4444 |
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+ | 0.0372 | 50.0 | 1350 | 6.2787 | 0.4444 |
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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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