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swin-tiny-patch4-window7-224-finetuned-wsdmhar

Image Classification
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  1. README.md +106 -16
  2. model.safetensors +1 -1
  3. runs/Jul26_05-06-21_DESKTOP-BJ85B6S/events.out.tfevents.1721959587.DESKTOP-BJ85B6S.19880.3 +2 -2
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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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:
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9297520661157025
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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
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # swin-tiny-patch4-window7-224-finetuned-wsdmhar
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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: 0.1990
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- - Accuracy: 0.9298
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  ## Model description
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@@ -61,22 +61,112 @@ The following hyperparameters were used during training:
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.7388 | 1.0 | 53 | 0.6308 | 0.7118 |
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- | 0.5099 | 2.0 | 106 | 0.3669 | 0.8485 |
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- | 0.4319 | 3.0 | 159 | 0.3324 | 0.8685 |
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- | 0.4002 | 4.0 | 212 | 0.2758 | 0.9029 |
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- | 0.3589 | 5.0 | 265 | 0.2503 | 0.9132 |
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- | 0.3096 | 6.0 | 318 | 0.2419 | 0.9136 |
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- | 0.2708 | 7.0 | 371 | 0.2277 | 0.9232 |
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- | 0.261 | 8.0 | 424 | 0.2168 | 0.9253 |
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- | 0.2526 | 9.0 | 477 | 0.2099 | 0.9246 |
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- | 0.2767 | 10.0 | 530 | 0.1990 | 0.9298 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: nielsr/swin-tiny-patch4-window7-224-finetuned-eurosat
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9645316804407713
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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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  # swin-tiny-patch4-window7-224-finetuned-wsdmhar
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+ This model is a fine-tuned version of [nielsr/swin-tiny-patch4-window7-224-finetuned-eurosat](https://huggingface.co/nielsr/swin-tiny-patch4-window7-224-finetuned-eurosat) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1480
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+ - Accuracy: 0.9645
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  ## Model description
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.0624 | 1.0 | 53 | 0.8879 | 0.6092 |
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+ | 0.6893 | 2.0 | 106 | 0.6601 | 0.7090 |
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+ | 0.6152 | 3.0 | 159 | 0.5114 | 0.7855 |
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+ | 0.5456 | 4.0 | 212 | 0.3819 | 0.8423 |
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+ | 0.4673 | 5.0 | 265 | 0.3267 | 0.8719 |
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+ | 0.4166 | 6.0 | 318 | 0.2804 | 0.9039 |
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+ | 0.3757 | 7.0 | 371 | 0.2881 | 0.8994 |
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+ | 0.3798 | 8.0 | 424 | 0.2635 | 0.9032 |
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+ | 0.3303 | 9.0 | 477 | 0.2703 | 0.9074 |
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+ | 0.3346 | 10.0 | 530 | 0.2565 | 0.9005 |
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+ | 0.2971 | 11.0 | 583 | 0.2182 | 0.9311 |
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+ | 0.2992 | 12.0 | 636 | 0.2240 | 0.9256 |
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+ | 0.2637 | 13.0 | 689 | 0.2131 | 0.9239 |
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+ | 0.2653 | 14.0 | 742 | 0.1801 | 0.9397 |
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+ | 0.2472 | 15.0 | 795 | 0.1807 | 0.9377 |
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+ | 0.2263 | 16.0 | 848 | 0.1612 | 0.9466 |
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+ | 0.1786 | 17.0 | 901 | 0.1735 | 0.9418 |
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+ | 0.2103 | 18.0 | 954 | 0.1786 | 0.9463 |
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+ | 0.1725 | 19.0 | 1007 | 0.1631 | 0.9473 |
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+ | 0.1787 | 20.0 | 1060 | 0.1439 | 0.9532 |
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+ | 0.1924 | 21.0 | 1113 | 0.1388 | 0.9504 |
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+ | 0.1662 | 22.0 | 1166 | 0.1470 | 0.9508 |
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+ | 0.1724 | 23.0 | 1219 | 0.1538 | 0.9497 |
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+ | 0.1633 | 24.0 | 1272 | 0.1731 | 0.9384 |
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+ | 0.174 | 25.0 | 1325 | 0.1555 | 0.9539 |
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+ | 0.1657 | 26.0 | 1378 | 0.1542 | 0.9494 |
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+ | 0.1513 | 27.0 | 1431 | 0.1526 | 0.9508 |
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+ | 0.126 | 28.0 | 1484 | 0.1560 | 0.9511 |
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+ | 0.1508 | 29.0 | 1537 | 0.1607 | 0.9480 |
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+ | 0.1368 | 30.0 | 1590 | 0.1729 | 0.9435 |
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+ | 0.1166 | 31.0 | 1643 | 0.1555 | 0.9532 |
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+ | 0.1076 | 32.0 | 1696 | 0.1400 | 0.9580 |
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+ | 0.1189 | 33.0 | 1749 | 0.1419 | 0.9590 |
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+ | 0.1512 | 34.0 | 1802 | 0.1364 | 0.9580 |
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+ | 0.1323 | 35.0 | 1855 | 0.1497 | 0.9539 |
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+ | 0.1031 | 36.0 | 1908 | 0.1437 | 0.9580 |
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+ | 0.1215 | 37.0 | 1961 | 0.1460 | 0.9559 |
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+ | 0.1069 | 38.0 | 2014 | 0.1362 | 0.9601 |
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+ | 0.129 | 39.0 | 2067 | 0.1490 | 0.9590 |
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+ | 0.1202 | 40.0 | 2120 | 0.1616 | 0.9545 |
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+ | 0.1011 | 41.0 | 2173 | 0.1518 | 0.9570 |
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+ | 0.1092 | 42.0 | 2226 | 0.1308 | 0.9618 |
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+ | 0.1163 | 43.0 | 2279 | 0.1458 | 0.9590 |
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+ | 0.1074 | 44.0 | 2332 | 0.1414 | 0.9549 |
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+ | 0.0814 | 45.0 | 2385 | 0.1509 | 0.9580 |
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+ | 0.0985 | 46.0 | 2438 | 0.1287 | 0.9628 |
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+ | 0.0863 | 47.0 | 2491 | 0.1277 | 0.9625 |
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+ | 0.0932 | 48.0 | 2544 | 0.1453 | 0.9559 |
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+ | 0.0863 | 49.0 | 2597 | 0.1520 | 0.9566 |
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+ | 0.0887 | 50.0 | 2650 | 0.1279 | 0.9656 |
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+ | 0.0744 | 51.0 | 2703 | 0.1552 | 0.9566 |
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+ | 0.0928 | 52.0 | 2756 | 0.1465 | 0.9621 |
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+ | 0.0776 | 53.0 | 2809 | 0.1575 | 0.9583 |
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+ | 0.088 | 54.0 | 2862 | 0.1614 | 0.9563 |
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+ | 0.0909 | 55.0 | 2915 | 0.1312 | 0.9638 |
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+ | 0.089 | 56.0 | 2968 | 0.1357 | 0.9652 |
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+ | 0.0587 | 57.0 | 3021 | 0.1510 | 0.9614 |
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+ | 0.0931 | 58.0 | 3074 | 0.1466 | 0.9580 |
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+ | 0.0878 | 59.0 | 3127 | 0.1499 | 0.9590 |
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+ | 0.0725 | 60.0 | 3180 | 0.1524 | 0.9597 |
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+ | 0.0543 | 61.0 | 3233 | 0.1543 | 0.9583 |
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+ | 0.0773 | 62.0 | 3286 | 0.1513 | 0.9635 |
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+ | 0.0626 | 63.0 | 3339 | 0.1511 | 0.9601 |
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+ | 0.0649 | 64.0 | 3392 | 0.1467 | 0.9594 |
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+ | 0.0705 | 65.0 | 3445 | 0.1443 | 0.9590 |
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+ | 0.0737 | 66.0 | 3498 | 0.1361 | 0.9607 |
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+ | 0.0518 | 67.0 | 3551 | 0.1441 | 0.9594 |
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+ | 0.0502 | 68.0 | 3604 | 0.1535 | 0.9590 |
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+ | 0.0701 | 69.0 | 3657 | 0.1362 | 0.9663 |
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+ | 0.0826 | 70.0 | 3710 | 0.1492 | 0.9611 |
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+ | 0.0715 | 71.0 | 3763 | 0.1615 | 0.9625 |
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+ | 0.0635 | 72.0 | 3816 | 0.1488 | 0.9642 |
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+ | 0.0522 | 73.0 | 3869 | 0.1456 | 0.9621 |
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+ | 0.0485 | 74.0 | 3922 | 0.1386 | 0.9645 |
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+ | 0.0629 | 75.0 | 3975 | 0.1463 | 0.9632 |
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+ | 0.0568 | 76.0 | 4028 | 0.1472 | 0.9621 |
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+ | 0.0556 | 77.0 | 4081 | 0.1440 | 0.9659 |
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+ | 0.0547 | 78.0 | 4134 | 0.1421 | 0.9635 |
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+ | 0.0527 | 79.0 | 4187 | 0.1444 | 0.9683 |
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+ | 0.054 | 80.0 | 4240 | 0.1464 | 0.9628 |
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+ | 0.0641 | 81.0 | 4293 | 0.1491 | 0.9635 |
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+ | 0.0546 | 82.0 | 4346 | 0.1529 | 0.9611 |
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+ | 0.059 | 83.0 | 4399 | 0.1462 | 0.9652 |
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+ | 0.0485 | 84.0 | 4452 | 0.1567 | 0.9632 |
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+ | 0.0388 | 85.0 | 4505 | 0.1548 | 0.9621 |
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+ | 0.0421 | 86.0 | 4558 | 0.1484 | 0.9621 |
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+ | 0.0375 | 87.0 | 4611 | 0.1681 | 0.9597 |
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+ | 0.0376 | 88.0 | 4664 | 0.1513 | 0.9632 |
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+ | 0.0514 | 89.0 | 4717 | 0.1485 | 0.9642 |
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+ | 0.0598 | 90.0 | 4770 | 0.1541 | 0.9638 |
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+ | 0.0431 | 91.0 | 4823 | 0.1474 | 0.9628 |
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+ | 0.0432 | 92.0 | 4876 | 0.1498 | 0.9645 |
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+ | 0.0391 | 93.0 | 4929 | 0.1506 | 0.9645 |
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+ | 0.0408 | 94.0 | 4982 | 0.1462 | 0.9642 |
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+ | 0.0335 | 95.0 | 5035 | 0.1509 | 0.9652 |
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+ | 0.0447 | 96.0 | 5088 | 0.1508 | 0.9635 |
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+ | 0.0477 | 97.0 | 5141 | 0.1510 | 0.9635 |
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+ | 0.0504 | 98.0 | 5194 | 0.1510 | 0.9642 |
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+ | 0.0406 | 99.0 | 5247 | 0.1479 | 0.9649 |
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+ | 0.0343 | 100.0 | 5300 | 0.1480 | 0.9645 |
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  ### Framework versions
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