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hushem_1x_deit_small_adamax_00001_fold5

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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-small-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_small_adamax_00001_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: 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: 0.6585365853658537
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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_small_adamax_00001_fold5
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+
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+ This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7730
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+ - Accuracy: 0.6585
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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 | 1.3080 | 0.3171 |
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+ | 1.348 | 2.0 | 12 | 1.2421 | 0.3659 |
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+ | 1.348 | 3.0 | 18 | 1.1840 | 0.4634 |
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+ | 1.1221 | 4.0 | 24 | 1.1443 | 0.4634 |
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+ | 0.9962 | 5.0 | 30 | 1.1209 | 0.4634 |
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+ | 0.9962 | 6.0 | 36 | 1.0884 | 0.5366 |
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+ | 0.8532 | 7.0 | 42 | 1.0512 | 0.5122 |
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+ | 0.8532 | 8.0 | 48 | 1.0147 | 0.5366 |
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+ | 0.73 | 9.0 | 54 | 0.9886 | 0.5366 |
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+ | 0.61 | 10.0 | 60 | 0.9683 | 0.5610 |
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+ | 0.61 | 11.0 | 66 | 0.9452 | 0.5854 |
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+ | 0.5241 | 12.0 | 72 | 0.9201 | 0.6341 |
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+ | 0.5241 | 13.0 | 78 | 0.9013 | 0.6341 |
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+ | 0.4293 | 14.0 | 84 | 0.8851 | 0.6341 |
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+ | 0.3674 | 15.0 | 90 | 0.8707 | 0.6341 |
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+ | 0.3674 | 16.0 | 96 | 0.8542 | 0.6341 |
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+ | 0.304 | 17.0 | 102 | 0.8474 | 0.6341 |
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+ | 0.304 | 18.0 | 108 | 0.8370 | 0.6341 |
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+ | 0.2449 | 19.0 | 114 | 0.8233 | 0.6341 |
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+ | 0.2119 | 20.0 | 120 | 0.8193 | 0.6341 |
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+ | 0.2119 | 21.0 | 126 | 0.8116 | 0.6341 |
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+ | 0.1788 | 22.0 | 132 | 0.8051 | 0.6341 |
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+ | 0.1788 | 23.0 | 138 | 0.7954 | 0.6341 |
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+ | 0.1445 | 24.0 | 144 | 0.7897 | 0.6341 |
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+ | 0.1262 | 25.0 | 150 | 0.7881 | 0.6829 |
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+ | 0.1262 | 26.0 | 156 | 0.7818 | 0.6585 |
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+ | 0.1066 | 27.0 | 162 | 0.7872 | 0.6829 |
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+ | 0.1066 | 28.0 | 168 | 0.7762 | 0.6585 |
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+ | 0.0891 | 29.0 | 174 | 0.7687 | 0.6585 |
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+ | 0.0806 | 30.0 | 180 | 0.7658 | 0.6829 |
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+ | 0.0806 | 31.0 | 186 | 0.7688 | 0.6829 |
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+ | 0.0692 | 32.0 | 192 | 0.7732 | 0.6829 |
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+ | 0.0692 | 33.0 | 198 | 0.7763 | 0.6585 |
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+ | 0.0592 | 34.0 | 204 | 0.7749 | 0.6585 |
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+ | 0.0587 | 35.0 | 210 | 0.7694 | 0.6829 |
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+ | 0.0587 | 36.0 | 216 | 0.7701 | 0.6829 |
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+ | 0.0549 | 37.0 | 222 | 0.7733 | 0.6585 |
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+ | 0.0549 | 38.0 | 228 | 0.7741 | 0.6585 |
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+ | 0.0463 | 39.0 | 234 | 0.7744 | 0.6585 |
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+ | 0.0481 | 40.0 | 240 | 0.7732 | 0.6585 |
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+ | 0.0481 | 41.0 | 246 | 0.7732 | 0.6585 |
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+ | 0.0468 | 42.0 | 252 | 0.7730 | 0.6585 |
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+ | 0.0468 | 43.0 | 258 | 0.7730 | 0.6585 |
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+ | 0.0455 | 44.0 | 264 | 0.7730 | 0.6585 |
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+ | 0.0473 | 45.0 | 270 | 0.7730 | 0.6585 |
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+ | 0.0473 | 46.0 | 276 | 0.7730 | 0.6585 |
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+ | 0.0444 | 47.0 | 282 | 0.7730 | 0.6585 |
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+ | 0.0444 | 48.0 | 288 | 0.7730 | 0.6585 |
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+ | 0.048 | 49.0 | 294 | 0.7730 | 0.6585 |
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+ | 0.0476 | 50.0 | 300 | 0.7730 | 0.6585 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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