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hushem_5x_deit_base_adamax_00001_fold4

Image Classification
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  2. model.safetensors +1 -1
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_adamax_00001_fold4
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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: 0.9285714285714286
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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_adamax_00001_fold4
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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: 0.2070
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+ - Accuracy: 0.9286
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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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+ | 1.2779 | 1.0 | 28 | 1.2578 | 0.5 |
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+ | 0.9904 | 2.0 | 56 | 1.0864 | 0.5952 |
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+ | 0.7136 | 3.0 | 84 | 0.8757 | 0.7381 |
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+ | 0.5283 | 4.0 | 112 | 0.7271 | 0.8095 |
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+ | 0.3401 | 5.0 | 140 | 0.5900 | 0.8333 |
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+ | 0.2667 | 6.0 | 168 | 0.4970 | 0.8571 |
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+ | 0.1719 | 7.0 | 196 | 0.4291 | 0.8810 |
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+ | 0.1351 | 8.0 | 224 | 0.3736 | 0.8810 |
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+ | 0.0756 | 9.0 | 252 | 0.3239 | 0.8571 |
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+ | 0.0457 | 10.0 | 280 | 0.2724 | 0.9286 |
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+ | 0.0311 | 11.0 | 308 | 0.2513 | 0.9286 |
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+ | 0.0183 | 12.0 | 336 | 0.2397 | 0.9524 |
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+ | 0.0115 | 13.0 | 364 | 0.2242 | 0.9286 |
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+ | 0.0092 | 14.0 | 392 | 0.2124 | 0.9286 |
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+ | 0.0064 | 15.0 | 420 | 0.2027 | 0.9286 |
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+ | 0.0052 | 16.0 | 448 | 0.2099 | 0.9286 |
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+ | 0.0048 | 17.0 | 476 | 0.2208 | 0.9286 |
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+ | 0.0041 | 18.0 | 504 | 0.2156 | 0.9286 |
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+ | 0.0036 | 19.0 | 532 | 0.2081 | 0.9286 |
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+ | 0.0034 | 20.0 | 560 | 0.2100 | 0.9286 |
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+ | 0.003 | 21.0 | 588 | 0.2099 | 0.9286 |
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+ | 0.0028 | 22.0 | 616 | 0.2113 | 0.9286 |
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+ | 0.0024 | 23.0 | 644 | 0.2110 | 0.9286 |
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+ | 0.0023 | 24.0 | 672 | 0.2106 | 0.9286 |
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+ | 0.0022 | 25.0 | 700 | 0.2101 | 0.9286 |
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+ | 0.002 | 26.0 | 728 | 0.2088 | 0.9286 |
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+ | 0.002 | 27.0 | 756 | 0.2066 | 0.9286 |
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+ | 0.0018 | 28.0 | 784 | 0.2096 | 0.9286 |
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+ | 0.0018 | 29.0 | 812 | 0.2064 | 0.9286 |
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+ | 0.0016 | 30.0 | 840 | 0.2088 | 0.9286 |
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+ | 0.0016 | 31.0 | 868 | 0.2088 | 0.9286 |
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+ | 0.0015 | 32.0 | 896 | 0.2078 | 0.9286 |
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+ | 0.0015 | 33.0 | 924 | 0.2057 | 0.9286 |
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+ | 0.0014 | 34.0 | 952 | 0.2073 | 0.9286 |
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+ | 0.0014 | 35.0 | 980 | 0.2070 | 0.9286 |
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+ | 0.0014 | 36.0 | 1008 | 0.2069 | 0.9286 |
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+ | 0.0013 | 37.0 | 1036 | 0.2071 | 0.9286 |
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+ | 0.0013 | 38.0 | 1064 | 0.2055 | 0.9286 |
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+ | 0.0013 | 39.0 | 1092 | 0.2077 | 0.9286 |
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+ | 0.0011 | 40.0 | 1120 | 0.2076 | 0.9286 |
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+ | 0.0012 | 41.0 | 1148 | 0.2068 | 0.9286 |
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+ | 0.0012 | 42.0 | 1176 | 0.2086 | 0.9286 |
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+ | 0.0011 | 43.0 | 1204 | 0.2084 | 0.9286 |
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+ | 0.0011 | 44.0 | 1232 | 0.2077 | 0.9286 |
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+ | 0.0011 | 45.0 | 1260 | 0.2078 | 0.9286 |
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+ | 0.0011 | 46.0 | 1288 | 0.2072 | 0.9286 |
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+ | 0.0011 | 47.0 | 1316 | 0.2070 | 0.9286 |
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+ | 0.0011 | 48.0 | 1344 | 0.2070 | 0.9286 |
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+ | 0.0012 | 49.0 | 1372 | 0.2070 | 0.9286 |
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+ | 0.0011 | 50.0 | 1400 | 0.2070 | 0.9286 |
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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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