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hushem_1x_deit_small_adamax_001_fold1

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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_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: 0.4666666666666667
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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_001_fold1
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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: 2.0215
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+ - Accuracy: 0.4667
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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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+ | No log | 1.0 | 6 | 2.2870 | 0.2444 |
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+ | 2.1668 | 2.0 | 12 | 1.4669 | 0.2444 |
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+ | 2.1668 | 3.0 | 18 | 1.4980 | 0.2444 |
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+ | 1.4102 | 4.0 | 24 | 1.4751 | 0.2444 |
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+ | 1.4394 | 5.0 | 30 | 1.4286 | 0.2444 |
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+ | 1.4394 | 6.0 | 36 | 1.6019 | 0.2444 |
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+ | 1.3171 | 7.0 | 42 | 1.7291 | 0.2222 |
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+ | 1.3171 | 8.0 | 48 | 1.5314 | 0.3556 |
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+ | 1.2906 | 9.0 | 54 | 1.7281 | 0.2667 |
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+ | 1.2151 | 10.0 | 60 | 1.6012 | 0.2444 |
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+ | 1.2151 | 11.0 | 66 | 1.5621 | 0.4444 |
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+ | 1.1016 | 12.0 | 72 | 1.5069 | 0.2 |
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+ | 1.1016 | 13.0 | 78 | 1.5452 | 0.4222 |
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+ | 1.1085 | 14.0 | 84 | 1.5457 | 0.2889 |
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+ | 0.9838 | 15.0 | 90 | 1.7131 | 0.4 |
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+ | 0.9838 | 16.0 | 96 | 1.9947 | 0.2889 |
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+ | 1.003 | 17.0 | 102 | 1.7538 | 0.4222 |
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+ | 1.003 | 18.0 | 108 | 1.3632 | 0.4444 |
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+ | 0.846 | 19.0 | 114 | 1.7633 | 0.4 |
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+ | 0.7432 | 20.0 | 120 | 1.5259 | 0.4222 |
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+ | 0.7432 | 21.0 | 126 | 1.6982 | 0.4 |
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+ | 0.8111 | 22.0 | 132 | 1.4722 | 0.4 |
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+ | 0.8111 | 23.0 | 138 | 1.5772 | 0.4222 |
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+ | 0.6268 | 24.0 | 144 | 1.6621 | 0.4222 |
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+ | 0.5956 | 25.0 | 150 | 2.2283 | 0.4 |
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+ | 0.5956 | 26.0 | 156 | 1.5965 | 0.4667 |
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+ | 0.863 | 27.0 | 162 | 2.0067 | 0.4 |
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+ | 0.863 | 28.0 | 168 | 2.2609 | 0.3778 |
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+ | 0.575 | 29.0 | 174 | 1.7339 | 0.4222 |
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+ | 0.3505 | 30.0 | 180 | 1.6059 | 0.3778 |
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+ | 0.3505 | 31.0 | 186 | 1.7578 | 0.4444 |
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+ | 0.3884 | 32.0 | 192 | 1.8785 | 0.4444 |
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+ | 0.3884 | 33.0 | 198 | 1.5952 | 0.4222 |
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+ | 0.3742 | 34.0 | 204 | 1.9834 | 0.4444 |
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+ | 0.3113 | 35.0 | 210 | 1.8134 | 0.4222 |
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+ | 0.3113 | 36.0 | 216 | 2.1491 | 0.4 |
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+ | 0.4478 | 37.0 | 222 | 1.9419 | 0.4667 |
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+ | 0.4478 | 38.0 | 228 | 1.8426 | 0.4444 |
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+ | 0.1746 | 39.0 | 234 | 1.9349 | 0.4222 |
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+ | 0.1737 | 40.0 | 240 | 2.0085 | 0.4667 |
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+ | 0.1737 | 41.0 | 246 | 2.0238 | 0.4667 |
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+ | 0.1448 | 42.0 | 252 | 2.0215 | 0.4667 |
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+ | 0.1448 | 43.0 | 258 | 2.0215 | 0.4667 |
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+ | 0.1495 | 44.0 | 264 | 2.0215 | 0.4667 |
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+ | 0.1326 | 45.0 | 270 | 2.0215 | 0.4667 |
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+ | 0.1326 | 46.0 | 276 | 2.0215 | 0.4667 |
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+ | 0.1487 | 47.0 | 282 | 2.0215 | 0.4667 |
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+ | 0.1487 | 48.0 | 288 | 2.0215 | 0.4667 |
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+ | 0.1112 | 49.0 | 294 | 2.0215 | 0.4667 |
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+ | 0.1501 | 50.0 | 300 | 2.0215 | 0.4667 |
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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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