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ayubkfupm
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swin-tiny-patch4-window7-224-finetuned-st-wsdmhar-xyz-auc

Image Classification
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Safetensors
swin
Generated from Trainer
Eval Results
Inference Endpoints
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: microsoft/swin-tiny-patch4-window7-224
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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: swin-tiny-patch4-window7-224-finetuned-st-wsdmhar-xyz-auc
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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: train
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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: 0.9765840220385675
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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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+ # swin-tiny-patch4-window7-224-finetuned-st-wsdmhar-xyz-auc
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+
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+ This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1060
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+ - Accuracy: 0.9766
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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: 5e-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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 100
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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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+ | 1.586 | 1.0 | 53 | 1.4366 | 0.4559 |
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+ | 0.9024 | 2.0 | 106 | 0.7526 | 0.7018 |
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+ | 0.6157 | 3.0 | 159 | 0.5375 | 0.7944 |
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+ | 0.5165 | 4.0 | 212 | 0.4298 | 0.8306 |
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+ | 0.4315 | 5.0 | 265 | 0.3646 | 0.8609 |
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+ | 0.3687 | 6.0 | 318 | 0.3054 | 0.8877 |
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+ | 0.3352 | 7.0 | 371 | 0.2822 | 0.9005 |
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+ | 0.3186 | 8.0 | 424 | 0.2764 | 0.9043 |
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+ | 0.3155 | 9.0 | 477 | 0.2409 | 0.9215 |
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+ | 0.2824 | 10.0 | 530 | 0.2459 | 0.9236 |
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+ | 0.2575 | 11.0 | 583 | 0.2346 | 0.9129 |
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+ | 0.2384 | 12.0 | 636 | 0.2445 | 0.9012 |
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+ | 0.2117 | 13.0 | 689 | 0.1838 | 0.9342 |
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+ | 0.2172 | 14.0 | 742 | 0.1789 | 0.9384 |
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+ | 0.1918 | 15.0 | 795 | 0.1615 | 0.9480 |
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+ | 0.1909 | 16.0 | 848 | 0.1516 | 0.9473 |
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+ | 0.1911 | 17.0 | 901 | 0.1513 | 0.9494 |
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+ | 0.2124 | 18.0 | 954 | 0.1524 | 0.9494 |
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+ | 0.1631 | 19.0 | 1007 | 0.1729 | 0.9339 |
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+ | 0.1766 | 20.0 | 1060 | 0.1329 | 0.9539 |
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+ | 0.168 | 21.0 | 1113 | 0.1235 | 0.9590 |
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+ | 0.1227 | 22.0 | 1166 | 0.1390 | 0.9483 |
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+ | 0.1705 | 23.0 | 1219 | 0.1290 | 0.9566 |
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+ | 0.1296 | 24.0 | 1272 | 0.1119 | 0.9621 |
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+ | 0.1201 | 25.0 | 1325 | 0.1452 | 0.9497 |
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+ | 0.1233 | 26.0 | 1378 | 0.1440 | 0.9487 |
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+ | 0.1412 | 27.0 | 1431 | 0.1206 | 0.9573 |
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+ | 0.1031 | 28.0 | 1484 | 0.1235 | 0.9580 |
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+ | 0.1131 | 29.0 | 1537 | 0.1377 | 0.9501 |
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+ | 0.1157 | 30.0 | 1590 | 0.1308 | 0.9580 |
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+ | 0.0925 | 31.0 | 1643 | 0.1172 | 0.9601 |
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+ | 0.0864 | 32.0 | 1696 | 0.1135 | 0.9621 |
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+ | 0.0748 | 33.0 | 1749 | 0.0987 | 0.9656 |
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+ | 0.1004 | 34.0 | 1802 | 0.0924 | 0.9728 |
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+ | 0.0858 | 35.0 | 1855 | 0.1058 | 0.9659 |
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+ | 0.0976 | 36.0 | 1908 | 0.1180 | 0.9587 |
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+ | 0.0797 | 37.0 | 1961 | 0.1035 | 0.9676 |
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+ | 0.0884 | 38.0 | 2014 | 0.0909 | 0.9707 |
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+ | 0.0841 | 39.0 | 2067 | 0.0979 | 0.9707 |
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+ | 0.0633 | 40.0 | 2120 | 0.0943 | 0.9697 |
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+ | 0.0601 | 41.0 | 2173 | 0.1017 | 0.9687 |
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+ | 0.0693 | 42.0 | 2226 | 0.1160 | 0.9652 |
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+ | 0.0715 | 43.0 | 2279 | 0.0980 | 0.9704 |
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+ | 0.0807 | 44.0 | 2332 | 0.1030 | 0.9711 |
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+ | 0.0614 | 45.0 | 2385 | 0.0999 | 0.9707 |
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+ | 0.0639 | 46.0 | 2438 | 0.1265 | 0.9632 |
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+ | 0.0623 | 47.0 | 2491 | 0.1195 | 0.9614 |
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+ | 0.0444 | 48.0 | 2544 | 0.1338 | 0.9659 |
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+ | 0.0551 | 49.0 | 2597 | 0.1042 | 0.9728 |
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+ | 0.0588 | 50.0 | 2650 | 0.0987 | 0.9731 |
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+ | 0.0421 | 51.0 | 2703 | 0.1306 | 0.9607 |
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+ | 0.0446 | 52.0 | 2756 | 0.1035 | 0.9718 |
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+ | 0.0489 | 53.0 | 2809 | 0.1084 | 0.9714 |
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+ | 0.0529 | 54.0 | 2862 | 0.1225 | 0.9663 |
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+ | 0.0403 | 55.0 | 2915 | 0.1053 | 0.9711 |
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+ | 0.0455 | 56.0 | 2968 | 0.1436 | 0.9645 |
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+ | 0.0436 | 57.0 | 3021 | 0.1052 | 0.9714 |
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+ | 0.0416 | 58.0 | 3074 | 0.1132 | 0.9666 |
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+ | 0.0378 | 59.0 | 3127 | 0.1055 | 0.9721 |
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+ | 0.0545 | 60.0 | 3180 | 0.1166 | 0.9704 |
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+ | 0.0315 | 61.0 | 3233 | 0.1073 | 0.9711 |
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+ | 0.0433 | 62.0 | 3286 | 0.1012 | 0.9735 |
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+ | 0.0577 | 63.0 | 3339 | 0.1117 | 0.9714 |
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+ | 0.0369 | 64.0 | 3392 | 0.1150 | 0.9697 |
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+ | 0.0459 | 65.0 | 3445 | 0.1054 | 0.9731 |
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+ | 0.0458 | 66.0 | 3498 | 0.1045 | 0.9745 |
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+ | 0.0374 | 67.0 | 3551 | 0.1105 | 0.9725 |
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+ | 0.0318 | 68.0 | 3604 | 0.1138 | 0.9718 |
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+ | 0.0337 | 69.0 | 3657 | 0.1053 | 0.9728 |
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+ | 0.0337 | 70.0 | 3710 | 0.1011 | 0.9738 |
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+ | 0.0329 | 71.0 | 3763 | 0.1067 | 0.9738 |
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+ | 0.0313 | 72.0 | 3816 | 0.1003 | 0.9756 |
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+ | 0.0446 | 73.0 | 3869 | 0.1125 | 0.9714 |
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+ | 0.047 | 74.0 | 3922 | 0.1040 | 0.9707 |
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+ | 0.0256 | 75.0 | 3975 | 0.1165 | 0.9700 |
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+ | 0.0535 | 76.0 | 4028 | 0.1129 | 0.9697 |
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+ | 0.029 | 77.0 | 4081 | 0.1040 | 0.9752 |
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+ | 0.044 | 78.0 | 4134 | 0.1116 | 0.9718 |
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+ | 0.0405 | 79.0 | 4187 | 0.1130 | 0.9725 |
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+ | 0.0417 | 80.0 | 4240 | 0.1094 | 0.9735 |
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+ | 0.0257 | 81.0 | 4293 | 0.1143 | 0.9697 |
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+ | 0.0293 | 82.0 | 4346 | 0.1111 | 0.9735 |
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+ | 0.0234 | 83.0 | 4399 | 0.1253 | 0.9704 |
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+ | 0.0295 | 84.0 | 4452 | 0.1133 | 0.9749 |
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+ | 0.0261 | 85.0 | 4505 | 0.1048 | 0.9738 |
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+ | 0.0215 | 86.0 | 4558 | 0.1072 | 0.9728 |
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+ | 0.0304 | 87.0 | 4611 | 0.1061 | 0.9731 |
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+ | 0.02 | 88.0 | 4664 | 0.1072 | 0.9742 |
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+ | 0.0353 | 89.0 | 4717 | 0.1096 | 0.9738 |
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+ | 0.0317 | 90.0 | 4770 | 0.1097 | 0.9745 |
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+ | 0.0441 | 91.0 | 4823 | 0.1080 | 0.9745 |
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+ | 0.0262 | 92.0 | 4876 | 0.1051 | 0.9752 |
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+ | 0.0312 | 93.0 | 4929 | 0.1089 | 0.9738 |
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+ | 0.025 | 94.0 | 4982 | 0.1094 | 0.9738 |
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+ | 0.0243 | 95.0 | 5035 | 0.1106 | 0.9745 |
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+ | 0.0245 | 96.0 | 5088 | 0.1076 | 0.9752 |
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+ | 0.0233 | 97.0 | 5141 | 0.1068 | 0.9762 |
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+ | 0.0279 | 98.0 | 5194 | 0.1063 | 0.9759 |
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+ | 0.0285 | 99.0 | 5247 | 0.1057 | 0.9766 |
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+ | 0.022 | 100.0 | 5300 | 0.1060 | 0.9766 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0.dev20240829+cu118
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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