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hushem_40x_deit_tiny_sgd_00001_fold5

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
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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-tiny-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_40x_deit_tiny_sgd_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: 0.1951219512195122
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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_40x_deit_tiny_sgd_00001_fold5
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5613
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+ - Accuracy: 0.1951
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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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+ | 1.4842 | 1.0 | 220 | 1.6446 | 0.1951 |
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+ | 1.5035 | 2.0 | 440 | 1.6414 | 0.1951 |
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+ | 1.4995 | 3.0 | 660 | 1.6381 | 0.1951 |
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+ | 1.5021 | 4.0 | 880 | 1.6349 | 0.1707 |
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+ | 1.454 | 5.0 | 1100 | 1.6317 | 0.1707 |
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+ | 1.4629 | 6.0 | 1320 | 1.6285 | 0.1707 |
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+ | 1.4161 | 7.0 | 1540 | 1.6253 | 0.1707 |
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+ | 1.4101 | 8.0 | 1760 | 1.6223 | 0.1707 |
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+ | 1.4149 | 9.0 | 1980 | 1.6192 | 0.1707 |
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+ | 1.4443 | 10.0 | 2200 | 1.6162 | 0.1707 |
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+ | 1.4163 | 11.0 | 2420 | 1.6133 | 0.1707 |
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+ | 1.4351 | 12.0 | 2640 | 1.6104 | 0.1707 |
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+ | 1.4104 | 13.0 | 2860 | 1.6076 | 0.1707 |
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+ | 1.3915 | 14.0 | 3080 | 1.6048 | 0.1707 |
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+ | 1.4251 | 15.0 | 3300 | 1.6022 | 0.1707 |
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+ | 1.4091 | 16.0 | 3520 | 1.5996 | 0.1951 |
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+ | 1.384 | 17.0 | 3740 | 1.5971 | 0.1951 |
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+ | 1.3979 | 18.0 | 3960 | 1.5947 | 0.1951 |
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+ | 1.3842 | 19.0 | 4180 | 1.5923 | 0.1951 |
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+ | 1.3555 | 20.0 | 4400 | 1.5900 | 0.1951 |
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+ | 1.3519 | 21.0 | 4620 | 1.5879 | 0.1951 |
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+ | 1.3873 | 22.0 | 4840 | 1.5859 | 0.1951 |
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+ | 1.3791 | 23.0 | 5060 | 1.5839 | 0.1951 |
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+ | 1.3799 | 24.0 | 5280 | 1.5820 | 0.1951 |
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+ | 1.3568 | 25.0 | 5500 | 1.5802 | 0.1951 |
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+ | 1.369 | 26.0 | 5720 | 1.5786 | 0.1951 |
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+ | 1.3732 | 27.0 | 5940 | 1.5770 | 0.1951 |
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+ | 1.3491 | 28.0 | 6160 | 1.5754 | 0.1951 |
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+ | 1.3457 | 29.0 | 6380 | 1.5740 | 0.1951 |
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+ | 1.3169 | 30.0 | 6600 | 1.5726 | 0.1951 |
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+ | 1.3748 | 31.0 | 6820 | 1.5714 | 0.1951 |
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+ | 1.3384 | 32.0 | 7040 | 1.5702 | 0.1951 |
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+ | 1.3281 | 33.0 | 7260 | 1.5691 | 0.1951 |
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+ | 1.3359 | 34.0 | 7480 | 1.5681 | 0.1951 |
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+ | 1.3414 | 35.0 | 7700 | 1.5671 | 0.1951 |
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+ | 1.3339 | 36.0 | 7920 | 1.5662 | 0.1951 |
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+ | 1.3778 | 37.0 | 8140 | 1.5654 | 0.1951 |
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+ | 1.3669 | 38.0 | 8360 | 1.5647 | 0.1951 |
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+ | 1.3509 | 39.0 | 8580 | 1.5641 | 0.1951 |
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+ | 1.3269 | 40.0 | 8800 | 1.5635 | 0.1951 |
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+ | 1.3717 | 41.0 | 9020 | 1.5630 | 0.1951 |
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+ | 1.3455 | 42.0 | 9240 | 1.5626 | 0.1951 |
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+ | 1.3737 | 43.0 | 9460 | 1.5622 | 0.1951 |
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+ | 1.3166 | 44.0 | 9680 | 1.5619 | 0.1951 |
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+ | 1.3504 | 45.0 | 9900 | 1.5617 | 0.1951 |
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+ | 1.3509 | 46.0 | 10120 | 1.5615 | 0.1951 |
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+ | 1.3526 | 47.0 | 10340 | 1.5614 | 0.1951 |
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+ | 1.3222 | 48.0 | 10560 | 1.5613 | 0.1951 |
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+ | 1.3165 | 49.0 | 10780 | 1.5613 | 0.1951 |
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+ | 1.3501 | 50.0 | 11000 | 1.5613 | 0.1951 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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