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hushem_40x_deit_base_sgd_0001_fold5

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
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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-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_40x_deit_base_sgd_0001_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: 0.5121951219512195
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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_base_sgd_0001_fold5
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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: 1.1678
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+ - Accuracy: 0.5122
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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: 0.0001
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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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+ | 1.3902 | 1.0 | 220 | 1.3668 | 0.2683 |
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+ | 1.375 | 2.0 | 440 | 1.3610 | 0.2927 |
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+ | 1.3643 | 3.0 | 660 | 1.3560 | 0.2683 |
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+ | 1.3352 | 4.0 | 880 | 1.3513 | 0.2683 |
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+ | 1.343 | 5.0 | 1100 | 1.3466 | 0.2683 |
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+ | 1.2985 | 6.0 | 1320 | 1.3416 | 0.2683 |
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+ | 1.3152 | 7.0 | 1540 | 1.3365 | 0.2927 |
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+ | 1.2618 | 8.0 | 1760 | 1.3311 | 0.3171 |
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+ | 1.2728 | 9.0 | 1980 | 1.3254 | 0.3415 |
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+ | 1.2604 | 10.0 | 2200 | 1.3195 | 0.3415 |
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+ | 1.2446 | 11.0 | 2420 | 1.3136 | 0.3415 |
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+ | 1.2322 | 12.0 | 2640 | 1.3076 | 0.3902 |
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+ | 1.2519 | 13.0 | 2860 | 1.3017 | 0.4146 |
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+ | 1.2115 | 14.0 | 3080 | 1.2958 | 0.4146 |
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+ | 1.2112 | 15.0 | 3300 | 1.2899 | 0.4390 |
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+ | 1.1892 | 16.0 | 3520 | 1.2841 | 0.4390 |
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+ | 1.1942 | 17.0 | 3740 | 1.2784 | 0.4390 |
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+ | 1.2008 | 18.0 | 3960 | 1.2727 | 0.4390 |
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+ | 1.1853 | 19.0 | 4180 | 1.2671 | 0.4390 |
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+ | 1.1573 | 20.0 | 4400 | 1.2615 | 0.4634 |
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+ | 1.1577 | 21.0 | 4620 | 1.2560 | 0.4634 |
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+ | 1.1317 | 22.0 | 4840 | 1.2506 | 0.4634 |
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+ | 1.1597 | 23.0 | 5060 | 1.2453 | 0.4878 |
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+ | 1.1283 | 24.0 | 5280 | 1.2401 | 0.4878 |
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+ | 1.1168 | 25.0 | 5500 | 1.2349 | 0.4634 |
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+ | 1.142 | 26.0 | 5720 | 1.2300 | 0.4634 |
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+ | 1.1324 | 27.0 | 5940 | 1.2251 | 0.4634 |
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+ | 1.1074 | 28.0 | 6160 | 1.2203 | 0.4634 |
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+ | 1.107 | 29.0 | 6380 | 1.2157 | 0.4634 |
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+ | 1.098 | 30.0 | 6600 | 1.2113 | 0.4634 |
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+ | 1.1034 | 31.0 | 6820 | 1.2071 | 0.4634 |
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+ | 1.0941 | 32.0 | 7040 | 1.2031 | 0.4634 |
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+ | 1.0839 | 33.0 | 7260 | 1.1993 | 0.4634 |
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+ | 1.0528 | 34.0 | 7480 | 1.1956 | 0.4634 |
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+ | 1.0292 | 35.0 | 7700 | 1.1922 | 0.4634 |
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+ | 1.0585 | 36.0 | 7920 | 1.1890 | 0.4634 |
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+ | 1.0434 | 37.0 | 8140 | 1.1859 | 0.4634 |
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+ | 1.0597 | 38.0 | 8360 | 1.1831 | 0.4634 |
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+ | 1.0626 | 39.0 | 8580 | 1.1805 | 0.4634 |
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+ | 1.0375 | 40.0 | 8800 | 1.1782 | 0.4634 |
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+ | 1.0422 | 41.0 | 9020 | 1.1761 | 0.4634 |
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+ | 1.0304 | 42.0 | 9240 | 1.1742 | 0.4634 |
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+ | 1.0373 | 43.0 | 9460 | 1.1726 | 0.4878 |
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+ | 1.0134 | 44.0 | 9680 | 1.1712 | 0.4878 |
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+ | 1.0323 | 45.0 | 9900 | 1.1701 | 0.4878 |
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+ | 1.0327 | 46.0 | 10120 | 1.1692 | 0.5122 |
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+ | 1.0599 | 47.0 | 10340 | 1.1685 | 0.5122 |
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+ | 1.0079 | 48.0 | 10560 | 1.1681 | 0.5122 |
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+ | 1.0145 | 49.0 | 10780 | 1.1679 | 0.5122 |
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+ | 1.0358 | 50.0 | 11000 | 1.1678 | 0.5122 |
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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 2.1.0+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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