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hushem_1x_deit_base_rms_0001_fold3

Image Classification
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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_1x_deit_base_rms_0001_fold3
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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: 0.5116279069767442
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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_deit_base_rms_0001_fold3
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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: 2.5728
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+ - Accuracy: 0.5116
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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: 0.0001
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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 | 1.5927 | 0.2558 |
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+ | 1.8022 | 2.0 | 12 | 1.4288 | 0.2558 |
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+ | 1.8022 | 3.0 | 18 | 1.5308 | 0.2558 |
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+ | 1.5239 | 4.0 | 24 | 1.4740 | 0.2558 |
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+ | 1.4801 | 5.0 | 30 | 2.2308 | 0.2558 |
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+ | 1.4801 | 6.0 | 36 | 1.4153 | 0.2558 |
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+ | 1.5953 | 7.0 | 42 | 1.4884 | 0.2326 |
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+ | 1.5953 | 8.0 | 48 | 1.5775 | 0.2558 |
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+ | 1.4262 | 9.0 | 54 | 1.4549 | 0.2558 |
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+ | 1.4607 | 10.0 | 60 | 1.4401 | 0.2558 |
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+ | 1.4607 | 11.0 | 66 | 1.3707 | 0.3256 |
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+ | 1.3771 | 12.0 | 72 | 1.3285 | 0.3721 |
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+ | 1.3771 | 13.0 | 78 | 1.2980 | 0.3721 |
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+ | 1.2887 | 14.0 | 84 | 1.6464 | 0.2558 |
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+ | 1.194 | 15.0 | 90 | 1.4572 | 0.2791 |
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+ | 1.194 | 16.0 | 96 | 1.5171 | 0.3256 |
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+ | 1.2311 | 17.0 | 102 | 1.4178 | 0.4186 |
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+ | 1.2311 | 18.0 | 108 | 1.3427 | 0.3256 |
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+ | 1.2234 | 19.0 | 114 | 1.3369 | 0.3721 |
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+ | 1.1384 | 20.0 | 120 | 1.4187 | 0.3721 |
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+ | 1.1384 | 21.0 | 126 | 1.5195 | 0.2558 |
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+ | 1.0551 | 22.0 | 132 | 1.5010 | 0.3488 |
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+ | 1.0551 | 23.0 | 138 | 1.4046 | 0.3721 |
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+ | 0.958 | 24.0 | 144 | 1.2991 | 0.3721 |
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+ | 0.9405 | 25.0 | 150 | 1.3687 | 0.4651 |
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+ | 0.9405 | 26.0 | 156 | 1.8052 | 0.3256 |
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+ | 0.7255 | 27.0 | 162 | 1.6391 | 0.4419 |
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+ | 0.7255 | 28.0 | 168 | 1.3419 | 0.5116 |
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+ | 0.6435 | 29.0 | 174 | 1.7678 | 0.4419 |
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+ | 0.4939 | 30.0 | 180 | 2.2022 | 0.3256 |
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+ | 0.4939 | 31.0 | 186 | 1.6603 | 0.5116 |
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+ | 0.4434 | 32.0 | 192 | 1.5952 | 0.4884 |
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+ | 0.4434 | 33.0 | 198 | 1.7642 | 0.5116 |
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+ | 0.2864 | 34.0 | 204 | 2.0069 | 0.4651 |
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+ | 0.1858 | 35.0 | 210 | 2.5370 | 0.4884 |
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+ | 0.1858 | 36.0 | 216 | 2.2076 | 0.4651 |
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+ | 0.1248 | 37.0 | 222 | 2.7233 | 0.5581 |
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+ | 0.1248 | 38.0 | 228 | 2.6548 | 0.5349 |
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+ | 0.0495 | 39.0 | 234 | 2.4864 | 0.5116 |
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+ | 0.0526 | 40.0 | 240 | 2.5601 | 0.5116 |
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+ | 0.0526 | 41.0 | 246 | 2.5731 | 0.5116 |
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+ | 0.0219 | 42.0 | 252 | 2.5728 | 0.5116 |
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+ | 0.0219 | 43.0 | 258 | 2.5728 | 0.5116 |
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+ | 0.0327 | 44.0 | 264 | 2.5728 | 0.5116 |
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+ | 0.0324 | 45.0 | 270 | 2.5728 | 0.5116 |
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+ | 0.0324 | 46.0 | 276 | 2.5728 | 0.5116 |
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+ | 0.0326 | 47.0 | 282 | 2.5728 | 0.5116 |
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+ | 0.0326 | 48.0 | 288 | 2.5728 | 0.5116 |
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+ | 0.0208 | 49.0 | 294 | 2.5728 | 0.5116 |
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+ | 0.0503 | 50.0 | 300 | 2.5728 | 0.5116 |
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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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