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hushem_5x_deit_base_rms_0001_fold2

Image Classification
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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_5x_deit_base_rms_0001_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: 0.5333333333333333
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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_rms_0001_fold2
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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: 5.1764
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+ - Accuracy: 0.5333
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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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+ | 1.4732 | 1.0 | 27 | 1.5871 | 0.2667 |
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+ | 1.4137 | 2.0 | 54 | 1.4271 | 0.2667 |
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+ | 1.462 | 3.0 | 81 | 1.4098 | 0.2667 |
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+ | 1.4423 | 4.0 | 108 | 1.4316 | 0.2444 |
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+ | 1.4677 | 5.0 | 135 | 1.1736 | 0.6 |
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+ | 1.1753 | 6.0 | 162 | 1.3090 | 0.4889 |
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+ | 1.0628 | 7.0 | 189 | 1.1008 | 0.4 |
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+ | 0.8856 | 8.0 | 216 | 1.3194 | 0.4667 |
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+ | 0.7266 | 9.0 | 243 | 1.5517 | 0.4667 |
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+ | 0.7206 | 10.0 | 270 | 1.5964 | 0.4222 |
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+ | 0.6825 | 11.0 | 297 | 1.9511 | 0.5333 |
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+ | 0.6024 | 12.0 | 324 | 1.1289 | 0.5111 |
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+ | 0.7093 | 13.0 | 351 | 1.6051 | 0.4667 |
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+ | 0.5446 | 14.0 | 378 | 1.0604 | 0.5333 |
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+ | 0.4716 | 15.0 | 405 | 2.6293 | 0.5778 |
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+ | 0.4728 | 16.0 | 432 | 3.2908 | 0.4889 |
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+ | 0.5099 | 17.0 | 459 | 2.0246 | 0.5333 |
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+ | 0.4809 | 18.0 | 486 | 3.4545 | 0.5333 |
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+ | 0.3484 | 19.0 | 513 | 2.2451 | 0.5111 |
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+ | 0.352 | 20.0 | 540 | 2.8572 | 0.4889 |
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+ | 0.3258 | 21.0 | 567 | 3.5970 | 0.5556 |
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+ | 0.2785 | 22.0 | 594 | 3.6404 | 0.5556 |
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+ | 0.3005 | 23.0 | 621 | 3.6333 | 0.5111 |
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+ | 0.2089 | 24.0 | 648 | 4.2561 | 0.5333 |
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+ | 0.1996 | 25.0 | 675 | 3.8526 | 0.5111 |
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+ | 0.1044 | 26.0 | 702 | 4.1245 | 0.5333 |
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+ | 0.2042 | 27.0 | 729 | 3.9154 | 0.5556 |
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+ | 0.1371 | 28.0 | 756 | 3.3906 | 0.5556 |
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+ | 0.1014 | 29.0 | 783 | 4.2534 | 0.5556 |
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+ | 0.0761 | 30.0 | 810 | 3.8328 | 0.5778 |
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+ | 0.0321 | 31.0 | 837 | 4.5117 | 0.5556 |
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+ | 0.1194 | 32.0 | 864 | 4.5296 | 0.5333 |
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+ | 0.0072 | 33.0 | 891 | 4.9299 | 0.5333 |
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+ | 0.0276 | 34.0 | 918 | 5.0433 | 0.5111 |
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+ | 0.0121 | 35.0 | 945 | 4.9519 | 0.5333 |
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+ | 0.0051 | 36.0 | 972 | 4.9546 | 0.5333 |
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+ | 0.0001 | 37.0 | 999 | 4.9700 | 0.5111 |
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+ | 0.0001 | 38.0 | 1026 | 4.9962 | 0.5111 |
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+ | 0.0 | 39.0 | 1053 | 5.0319 | 0.5111 |
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+ | 0.0 | 40.0 | 1080 | 5.0566 | 0.5111 |
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+ | 0.0001 | 41.0 | 1107 | 5.0812 | 0.5333 |
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+ | 0.0 | 42.0 | 1134 | 5.1051 | 0.5333 |
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+ | 0.0 | 43.0 | 1161 | 5.1228 | 0.5333 |
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+ | 0.0 | 44.0 | 1188 | 5.1393 | 0.5333 |
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+ | 0.0 | 45.0 | 1215 | 5.1531 | 0.5333 |
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+ | 0.0 | 46.0 | 1242 | 5.1647 | 0.5333 |
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+ | 0.0 | 47.0 | 1269 | 5.1724 | 0.5333 |
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+ | 0.0 | 48.0 | 1296 | 5.1763 | 0.5333 |
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+ | 0.0 | 49.0 | 1323 | 5.1764 | 0.5333 |
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+ | 0.0 | 50.0 | 1350 | 5.1764 | 0.5333 |
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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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