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hushem_40x_deit_tiny_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-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_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_tiny_sgd_0001_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: 1.1237
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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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+ | 1.4318 | 1.0 | 220 | 1.6149 | 0.1707 |
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+ | 1.3729 | 2.0 | 440 | 1.5770 | 0.1951 |
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+ | 1.3561 | 3.0 | 660 | 1.5432 | 0.1707 |
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+ | 1.3096 | 4.0 | 880 | 1.5177 | 0.1463 |
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+ | 1.2756 | 5.0 | 1100 | 1.4946 | 0.1951 |
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+ | 1.2485 | 6.0 | 1320 | 1.4738 | 0.2195 |
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+ | 1.1719 | 7.0 | 1540 | 1.4569 | 0.2195 |
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+ | 1.1324 | 8.0 | 1760 | 1.4401 | 0.2439 |
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+ | 1.1522 | 9.0 | 1980 | 1.4251 | 0.2683 |
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+ | 1.1548 | 10.0 | 2200 | 1.4097 | 0.2439 |
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+ | 1.1099 | 11.0 | 2420 | 1.3960 | 0.2683 |
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+ | 1.0799 | 12.0 | 2640 | 1.3821 | 0.2683 |
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+ | 1.072 | 13.0 | 2860 | 1.3689 | 0.2927 |
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+ | 1.0381 | 14.0 | 3080 | 1.3552 | 0.3171 |
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+ | 1.0533 | 15.0 | 3300 | 1.3423 | 0.2927 |
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+ | 1.0294 | 16.0 | 3520 | 1.3293 | 0.3171 |
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+ | 1.004 | 17.0 | 3740 | 1.3169 | 0.3171 |
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+ | 1.0138 | 18.0 | 3960 | 1.3048 | 0.3171 |
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+ | 0.9902 | 19.0 | 4180 | 1.2935 | 0.3171 |
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+ | 0.9047 | 20.0 | 4400 | 1.2817 | 0.3171 |
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+ | 0.9213 | 21.0 | 4620 | 1.2707 | 0.3415 |
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+ | 0.9555 | 22.0 | 4840 | 1.2595 | 0.3415 |
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+ | 0.9607 | 23.0 | 5060 | 1.2491 | 0.3415 |
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+ | 0.9344 | 24.0 | 5280 | 1.2391 | 0.3415 |
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+ | 0.8688 | 25.0 | 5500 | 1.2295 | 0.3902 |
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+ | 0.9175 | 26.0 | 5720 | 1.2208 | 0.4146 |
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+ | 0.887 | 27.0 | 5940 | 1.2120 | 0.4390 |
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+ | 0.905 | 28.0 | 6160 | 1.2036 | 0.4634 |
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+ | 0.8477 | 29.0 | 6380 | 1.1957 | 0.4878 |
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+ | 0.8486 | 30.0 | 6600 | 1.1887 | 0.4878 |
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+ | 0.9203 | 31.0 | 6820 | 1.1822 | 0.4878 |
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+ | 0.8893 | 32.0 | 7040 | 1.1760 | 0.4878 |
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+ | 0.8469 | 33.0 | 7260 | 1.1702 | 0.4878 |
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+ | 0.7935 | 34.0 | 7480 | 1.1645 | 0.4878 |
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+ | 0.7904 | 35.0 | 7700 | 1.1593 | 0.4878 |
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+ | 0.7994 | 36.0 | 7920 | 1.1544 | 0.5122 |
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+ | 0.8205 | 37.0 | 8140 | 1.1499 | 0.5122 |
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+ | 0.8696 | 38.0 | 8360 | 1.1458 | 0.5122 |
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+ | 0.8262 | 39.0 | 8580 | 1.1421 | 0.5122 |
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+ | 0.7584 | 40.0 | 8800 | 1.1388 | 0.5122 |
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+ | 0.8457 | 41.0 | 9020 | 1.1358 | 0.5122 |
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+ | 0.8307 | 42.0 | 9240 | 1.1331 | 0.5122 |
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+ | 0.8183 | 43.0 | 9460 | 1.1307 | 0.5122 |
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+ | 0.7718 | 44.0 | 9680 | 1.1287 | 0.5122 |
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+ | 0.7855 | 45.0 | 9900 | 1.1271 | 0.5122 |
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+ | 0.7875 | 46.0 | 10120 | 1.1258 | 0.5122 |
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+ | 0.8109 | 47.0 | 10340 | 1.1248 | 0.5122 |
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+ | 0.7297 | 48.0 | 10560 | 1.1241 | 0.5122 |
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+ | 0.7352 | 49.0 | 10780 | 1.1238 | 0.5122 |
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+ | 0.7935 | 50.0 | 11000 | 1.1237 | 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 2.1.1+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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