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hushem_5x_deit_small_adamax_00001_fold2

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-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_5x_deit_small_adamax_00001_fold2
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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: 0.6888888888888889
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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_small_adamax_00001_fold2
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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: 1.4402
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+ - Accuracy: 0.6889
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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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+ | 1.2515 | 1.0 | 27 | 1.2615 | 0.5333 |
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+ | 0.9391 | 2.0 | 54 | 1.2122 | 0.5556 |
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+ | 0.6766 | 3.0 | 81 | 1.1537 | 0.5333 |
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+ | 0.5382 | 4.0 | 108 | 1.1591 | 0.6 |
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+ | 0.3747 | 5.0 | 135 | 1.0974 | 0.6444 |
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+ | 0.2681 | 6.0 | 162 | 1.0815 | 0.6444 |
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+ | 0.1892 | 7.0 | 189 | 1.1005 | 0.6222 |
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+ | 0.1214 | 8.0 | 216 | 1.0974 | 0.6222 |
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+ | 0.0863 | 9.0 | 243 | 1.0922 | 0.6444 |
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+ | 0.0475 | 10.0 | 270 | 1.1018 | 0.6667 |
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+ | 0.0299 | 11.0 | 297 | 1.1054 | 0.6889 |
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+ | 0.0156 | 12.0 | 324 | 1.1555 | 0.6667 |
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+ | 0.0095 | 13.0 | 351 | 1.1847 | 0.6667 |
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+ | 0.0067 | 14.0 | 378 | 1.2033 | 0.6667 |
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+ | 0.0051 | 15.0 | 405 | 1.2483 | 0.6667 |
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+ | 0.004 | 16.0 | 432 | 1.2613 | 0.6667 |
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+ | 0.0032 | 17.0 | 459 | 1.2726 | 0.6667 |
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+ | 0.0028 | 18.0 | 486 | 1.2843 | 0.6667 |
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+ | 0.0026 | 19.0 | 513 | 1.2998 | 0.6667 |
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+ | 0.0021 | 20.0 | 540 | 1.3093 | 0.6667 |
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+ | 0.0019 | 21.0 | 567 | 1.3233 | 0.6667 |
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+ | 0.0018 | 22.0 | 594 | 1.3315 | 0.6667 |
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+ | 0.0015 | 23.0 | 621 | 1.3379 | 0.6667 |
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+ | 0.0014 | 24.0 | 648 | 1.3489 | 0.6667 |
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+ | 0.0014 | 25.0 | 675 | 1.3547 | 0.6667 |
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+ | 0.0013 | 26.0 | 702 | 1.3608 | 0.6889 |
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+ | 0.0012 | 27.0 | 729 | 1.3706 | 0.6667 |
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+ | 0.0011 | 28.0 | 756 | 1.3780 | 0.6667 |
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+ | 0.0012 | 29.0 | 783 | 1.3808 | 0.6889 |
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+ | 0.0011 | 30.0 | 810 | 1.3868 | 0.6889 |
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+ | 0.001 | 31.0 | 837 | 1.3922 | 0.6889 |
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+ | 0.001 | 32.0 | 864 | 1.3991 | 0.6889 |
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+ | 0.0009 | 33.0 | 891 | 1.4019 | 0.6889 |
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+ | 0.0009 | 34.0 | 918 | 1.4078 | 0.6889 |
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+ | 0.0009 | 35.0 | 945 | 1.4120 | 0.6889 |
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+ | 0.0008 | 36.0 | 972 | 1.4161 | 0.6889 |
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+ | 0.0008 | 37.0 | 999 | 1.4179 | 0.6889 |
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+ | 0.0008 | 38.0 | 1026 | 1.4222 | 0.6889 |
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+ | 0.0007 | 39.0 | 1053 | 1.4264 | 0.6889 |
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+ | 0.0007 | 40.0 | 1080 | 1.4282 | 0.6889 |
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+ | 0.0007 | 41.0 | 1107 | 1.4320 | 0.6889 |
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+ | 0.0007 | 42.0 | 1134 | 1.4342 | 0.6889 |
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+ | 0.0007 | 43.0 | 1161 | 1.4365 | 0.6889 |
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+ | 0.0007 | 44.0 | 1188 | 1.4366 | 0.6889 |
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+ | 0.0007 | 45.0 | 1215 | 1.4383 | 0.6889 |
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+ | 0.0007 | 46.0 | 1242 | 1.4394 | 0.6889 |
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+ | 0.0007 | 47.0 | 1269 | 1.4399 | 0.6889 |
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+ | 0.0007 | 48.0 | 1296 | 1.4402 | 0.6889 |
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+ | 0.0007 | 49.0 | 1323 | 1.4402 | 0.6889 |
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+ | 0.0007 | 50.0 | 1350 | 1.4402 | 0.6889 |
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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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