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Plant_Classification_model_vit-base-patch16-224-in21k

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README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Professor/Plant_Classification_model_vit-base-patch16-224-in21k](https://huggingface.co/Professor/Plant_Classification_model_vit-base-patch16-224-in21k) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5046
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- - Accuracy: 0.7388
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  ## Model description
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@@ -44,212 +44,32 @@ 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_steps: 50
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- - num_epochs: 200
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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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- | No log | 1.0 | 65 | 1.7899 | 0.6140 |
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- | No log | 2.0 | 130 | 1.6077 | 0.6667 |
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- | No log | 3.0 | 195 | 1.6408 | 0.6511 |
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- | No log | 4.0 | 260 | 1.6168 | 0.6569 |
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- | No log | 5.0 | 325 | 1.5779 | 0.6784 |
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- | No log | 6.0 | 390 | 1.6319 | 0.6686 |
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- | No log | 7.0 | 455 | 1.5388 | 0.6940 |
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- | 1.4165 | 8.0 | 520 | 1.7726 | 0.6121 |
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- | 1.4165 | 9.0 | 585 | 1.6132 | 0.6764 |
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- | 1.4165 | 10.0 | 650 | 1.6917 | 0.6550 |
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- | 1.4165 | 11.0 | 715 | 1.6451 | 0.6647 |
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- | 1.4165 | 12.0 | 780 | 1.6586 | 0.6706 |
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- | 1.4165 | 13.0 | 845 | 1.5735 | 0.6998 |
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- | 1.4165 | 14.0 | 910 | 1.6301 | 0.6667 |
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- | 1.4165 | 15.0 | 975 | 1.5863 | 0.7018 |
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- | 0.9754 | 16.0 | 1040 | 1.6891 | 0.6608 |
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- | 0.9754 | 17.0 | 1105 | 1.6232 | 0.6823 |
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- | 0.9754 | 18.0 | 1170 | 1.6181 | 0.6940 |
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- | 0.9754 | 19.0 | 1235 | 1.6600 | 0.6803 |
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- | 0.9754 | 20.0 | 1300 | 1.6032 | 0.6823 |
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- | 0.9754 | 21.0 | 1365 | 1.5761 | 0.6901 |
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- | 0.9754 | 22.0 | 1430 | 1.5992 | 0.6998 |
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- | 0.9754 | 23.0 | 1495 | 1.7566 | 0.6335 |
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- | 0.8739 | 24.0 | 1560 | 1.6459 | 0.6706 |
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- | 0.8739 | 25.0 | 1625 | 1.7036 | 0.6530 |
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- | 0.8739 | 26.0 | 1690 | 1.6099 | 0.6998 |
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- | 0.8739 | 27.0 | 1755 | 1.5543 | 0.7154 |
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- | 0.8739 | 28.0 | 1820 | 1.6657 | 0.6686 |
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- | 0.8739 | 29.0 | 1885 | 1.6664 | 0.6764 |
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- | 0.8739 | 30.0 | 1950 | 1.7176 | 0.6589 |
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- | 0.8336 | 31.0 | 2015 | 1.7594 | 0.6374 |
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- | 0.8336 | 32.0 | 2080 | 1.7652 | 0.6394 |
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- | 0.8336 | 33.0 | 2145 | 1.6813 | 0.6706 |
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- | 0.8336 | 34.0 | 2210 | 1.6347 | 0.6823 |
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- | 0.8336 | 35.0 | 2275 | 1.6370 | 0.6959 |
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- | 0.8336 | 36.0 | 2340 | 1.5888 | 0.7096 |
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- | 0.8336 | 37.0 | 2405 | 1.6533 | 0.6901 |
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- | 0.8336 | 38.0 | 2470 | 1.7444 | 0.6550 |
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- | 0.8164 | 39.0 | 2535 | 1.6537 | 0.6784 |
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- | 0.8164 | 40.0 | 2600 | 1.6352 | 0.6940 |
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- | 0.8164 | 41.0 | 2665 | 1.6136 | 0.7037 |
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- | 0.8164 | 42.0 | 2730 | 1.6196 | 0.6979 |
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- | 0.8164 | 43.0 | 2795 | 1.6115 | 0.6901 |
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- | 0.8164 | 44.0 | 2860 | 1.6563 | 0.6842 |
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- | 0.8164 | 45.0 | 2925 | 1.6126 | 0.7018 |
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- | 0.8164 | 46.0 | 2990 | 1.6695 | 0.6745 |
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- | 0.8011 | 47.0 | 3055 | 1.6163 | 0.6881 |
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- | 0.8011 | 48.0 | 3120 | 1.6003 | 0.7076 |
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- | 0.8011 | 49.0 | 3185 | 1.6851 | 0.6647 |
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- | 0.8011 | 50.0 | 3250 | 1.6148 | 0.7018 |
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- | 0.8011 | 51.0 | 3315 | 1.6130 | 0.6920 |
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- | 0.8011 | 52.0 | 3380 | 1.6680 | 0.6784 |
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- | 0.8011 | 53.0 | 3445 | 1.6761 | 0.6823 |
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- | 0.8089 | 54.0 | 3510 | 1.7472 | 0.6413 |
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- | 0.8089 | 55.0 | 3575 | 1.7329 | 0.6491 |
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- | 0.8089 | 56.0 | 3640 | 1.7198 | 0.6608 |
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- | 0.8089 | 57.0 | 3705 | 1.6746 | 0.6842 |
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- | 0.8089 | 58.0 | 3770 | 1.5865 | 0.6979 |
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- | 0.8089 | 59.0 | 3835 | 1.5857 | 0.7096 |
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- | 0.8089 | 60.0 | 3900 | 1.6424 | 0.6940 |
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- | 0.8089 | 61.0 | 3965 | 1.6277 | 0.6959 |
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- | 0.793 | 62.0 | 4030 | 1.6282 | 0.6920 |
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- | 0.793 | 63.0 | 4095 | 1.6081 | 0.7037 |
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- | 0.793 | 64.0 | 4160 | 1.5735 | 0.7173 |
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- | 0.793 | 65.0 | 4225 | 1.5931 | 0.7115 |
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- | 0.793 | 66.0 | 4290 | 1.5654 | 0.7115 |
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- | 0.793 | 67.0 | 4355 | 1.6955 | 0.6764 |
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- | 0.793 | 68.0 | 4420 | 1.6564 | 0.6862 |
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- | 0.793 | 69.0 | 4485 | 1.6102 | 0.7018 |
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- | 0.7796 | 70.0 | 4550 | 1.6658 | 0.6784 |
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- | 0.7796 | 71.0 | 4615 | 1.6572 | 0.6745 |
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- | 0.7796 | 72.0 | 4680 | 1.5700 | 0.7115 |
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- | 0.7796 | 73.0 | 4745 | 1.6323 | 0.6823 |
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- | 0.7796 | 74.0 | 4810 | 1.6547 | 0.6803 |
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- | 0.7796 | 75.0 | 4875 | 1.5867 | 0.7096 |
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- | 0.7796 | 76.0 | 4940 | 1.6341 | 0.6940 |
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- | 0.7821 | 77.0 | 5005 | 1.5601 | 0.7212 |
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- | 0.7821 | 78.0 | 5070 | 1.5888 | 0.7154 |
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- | 0.7821 | 79.0 | 5135 | 1.6283 | 0.6998 |
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- | 0.7821 | 80.0 | 5200 | 1.5526 | 0.7173 |
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- | 0.7821 | 81.0 | 5265 | 1.6215 | 0.6940 |
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- | 0.7821 | 82.0 | 5330 | 1.6607 | 0.6862 |
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- | 0.7821 | 83.0 | 5395 | 1.6475 | 0.6823 |
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- | 0.7821 | 84.0 | 5460 | 1.6054 | 0.7096 |
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- | 0.7749 | 85.0 | 5525 | 1.6370 | 0.6959 |
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- | 0.7749 | 86.0 | 5590 | 1.6143 | 0.6998 |
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- | 0.7749 | 87.0 | 5655 | 1.6204 | 0.6920 |
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- | 0.7749 | 88.0 | 5720 | 1.6927 | 0.6803 |
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- | 0.7749 | 89.0 | 5785 | 1.6856 | 0.6784 |
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- | 0.7749 | 90.0 | 5850 | 1.6473 | 0.6959 |
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- | 0.7749 | 91.0 | 5915 | 1.6356 | 0.6940 |
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- | 0.7749 | 92.0 | 5980 | 1.6449 | 0.6881 |
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- | 0.7741 | 93.0 | 6045 | 1.6522 | 0.6940 |
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- | 0.7741 | 94.0 | 6110 | 1.7063 | 0.6686 |
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- | 0.7741 | 95.0 | 6175 | 1.7064 | 0.6803 |
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- | 0.7741 | 96.0 | 6240 | 1.6437 | 0.6998 |
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- | 0.7741 | 97.0 | 6305 | 1.6400 | 0.6881 |
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- | 0.7741 | 98.0 | 6370 | 1.6907 | 0.6706 |
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- | 0.7741 | 99.0 | 6435 | 1.6791 | 0.6803 |
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- | 0.7721 | 100.0 | 6500 | 1.6895 | 0.6803 |
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- | 0.7721 | 101.0 | 6565 | 1.6132 | 0.6998 |
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- | 0.7721 | 102.0 | 6630 | 1.6058 | 0.7037 |
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- | 0.7721 | 103.0 | 6695 | 1.6045 | 0.7154 |
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- | 0.7721 | 104.0 | 6760 | 1.5828 | 0.7173 |
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- | 0.7721 | 105.0 | 6825 | 1.6337 | 0.6920 |
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- | 0.7721 | 106.0 | 6890 | 1.6262 | 0.6979 |
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- | 0.7721 | 107.0 | 6955 | 1.6166 | 0.6979 |
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- | 0.7576 | 108.0 | 7020 | 1.5869 | 0.7154 |
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- | 0.7576 | 109.0 | 7085 | 1.6349 | 0.6959 |
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- | 0.7576 | 110.0 | 7150 | 1.5977 | 0.6998 |
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- | 0.7576 | 111.0 | 7215 | 1.6054 | 0.7018 |
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- | 0.7576 | 112.0 | 7280 | 1.6029 | 0.6979 |
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- | 0.7576 | 113.0 | 7345 | 1.6131 | 0.6959 |
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- | 0.7576 | 114.0 | 7410 | 1.6488 | 0.6803 |
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- | 0.7576 | 115.0 | 7475 | 1.6223 | 0.6979 |
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- | 0.7568 | 116.0 | 7540 | 1.6581 | 0.6745 |
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- | 0.7568 | 117.0 | 7605 | 1.5714 | 0.7115 |
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- | 0.7568 | 118.0 | 7670 | 1.5629 | 0.7193 |
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- | 0.7568 | 119.0 | 7735 | 1.5841 | 0.7018 |
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- | 0.7568 | 120.0 | 7800 | 1.6263 | 0.6881 |
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- | 0.7568 | 121.0 | 7865 | 1.5982 | 0.7018 |
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- | 0.7568 | 122.0 | 7930 | 1.6473 | 0.6881 |
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- | 0.7568 | 123.0 | 7995 | 1.6026 | 0.7018 |
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- | 0.7531 | 124.0 | 8060 | 1.5897 | 0.7057 |
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- | 0.7531 | 125.0 | 8125 | 1.6494 | 0.6784 |
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- | 0.7531 | 126.0 | 8190 | 1.5711 | 0.7173 |
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- | 0.7531 | 127.0 | 8255 | 1.5992 | 0.7076 |
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- | 0.7531 | 128.0 | 8320 | 1.5605 | 0.7154 |
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- | 0.7531 | 129.0 | 8385 | 1.5683 | 0.7115 |
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- | 0.7531 | 130.0 | 8450 | 1.6044 | 0.7096 |
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- | 0.7492 | 131.0 | 8515 | 1.5654 | 0.7232 |
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- | 0.7492 | 132.0 | 8580 | 1.6027 | 0.7057 |
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- | 0.7492 | 133.0 | 8645 | 1.6116 | 0.6998 |
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- | 0.7492 | 134.0 | 8710 | 1.6030 | 0.7057 |
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- | 0.7492 | 135.0 | 8775 | 1.6039 | 0.7018 |
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- | 0.7492 | 136.0 | 8840 | 1.5695 | 0.7154 |
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- | 0.7492 | 137.0 | 8905 | 1.6011 | 0.7018 |
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- | 0.7492 | 138.0 | 8970 | 1.6054 | 0.6959 |
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- | 0.7457 | 139.0 | 9035 | 1.6654 | 0.6842 |
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- | 0.7457 | 140.0 | 9100 | 1.6112 | 0.7076 |
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- | 0.7457 | 141.0 | 9165 | 1.5575 | 0.7251 |
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- | 0.7457 | 142.0 | 9230 | 1.5775 | 0.7173 |
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- | 0.7457 | 143.0 | 9295 | 1.5442 | 0.7310 |
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- | 0.7457 | 144.0 | 9360 | 1.5465 | 0.7232 |
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- | 0.7457 | 145.0 | 9425 | 1.5561 | 0.7251 |
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- | 0.7457 | 146.0 | 9490 | 1.5677 | 0.7193 |
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- | 0.7453 | 147.0 | 9555 | 1.5790 | 0.7135 |
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- | 0.7453 | 148.0 | 9620 | 1.5981 | 0.7057 |
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- | 0.7453 | 149.0 | 9685 | 1.5510 | 0.7232 |
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- | 0.7453 | 150.0 | 9750 | 1.5833 | 0.7154 |
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- | 0.7453 | 151.0 | 9815 | 1.5798 | 0.7212 |
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- | 0.7453 | 152.0 | 9880 | 1.5525 | 0.7232 |
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- | 0.7453 | 153.0 | 9945 | 1.5433 | 0.7212 |
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- | 0.7416 | 154.0 | 10010 | 1.5549 | 0.7232 |
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- | 0.7416 | 155.0 | 10075 | 1.5626 | 0.7173 |
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- | 0.7416 | 156.0 | 10140 | 1.5673 | 0.7212 |
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- | 0.7416 | 157.0 | 10205 | 1.5482 | 0.7290 |
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- | 0.7416 | 158.0 | 10270 | 1.5333 | 0.7290 |
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- | 0.7416 | 159.0 | 10335 | 1.5338 | 0.7271 |
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- | 0.7416 | 160.0 | 10400 | 1.5480 | 0.7193 |
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- | 0.7416 | 161.0 | 10465 | 1.5431 | 0.7271 |
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- | 0.7414 | 162.0 | 10530 | 1.5469 | 0.7251 |
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- | 0.7414 | 163.0 | 10595 | 1.5504 | 0.7232 |
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- | 0.7414 | 164.0 | 10660 | 1.5850 | 0.7173 |
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- | 0.7414 | 165.0 | 10725 | 1.5352 | 0.7251 |
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- | 0.7414 | 166.0 | 10790 | 1.5480 | 0.7290 |
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- | 0.7414 | 167.0 | 10855 | 1.5736 | 0.7173 |
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- | 0.7414 | 168.0 | 10920 | 1.5507 | 0.7251 |
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- | 0.7414 | 169.0 | 10985 | 1.5347 | 0.7251 |
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- | 0.7411 | 170.0 | 11050 | 1.5355 | 0.7349 |
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- | 0.7411 | 171.0 | 11115 | 1.5273 | 0.7388 |
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- | 0.7411 | 172.0 | 11180 | 1.5286 | 0.7349 |
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- | 0.7411 | 173.0 | 11245 | 1.5664 | 0.7212 |
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- | 0.7411 | 174.0 | 11310 | 1.5340 | 0.7310 |
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- | 0.7411 | 175.0 | 11375 | 1.5311 | 0.7388 |
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- | 0.7411 | 176.0 | 11440 | 1.5405 | 0.7329 |
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- | 0.7395 | 177.0 | 11505 | 1.5261 | 0.7388 |
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- | 0.7395 | 178.0 | 11570 | 1.5289 | 0.7388 |
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- | 0.7395 | 179.0 | 11635 | 1.5303 | 0.7368 |
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- | 0.7395 | 180.0 | 11700 | 1.5323 | 0.7349 |
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- | 0.7395 | 181.0 | 11765 | 1.5374 | 0.7310 |
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- | 0.7395 | 182.0 | 11830 | 1.5357 | 0.7349 |
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- | 0.7395 | 183.0 | 11895 | 1.5442 | 0.7310 |
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- | 0.7395 | 184.0 | 11960 | 1.5453 | 0.7310 |
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- | 0.7396 | 185.0 | 12025 | 1.5130 | 0.7388 |
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- | 0.7396 | 186.0 | 12090 | 1.5179 | 0.7407 |
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- | 0.7396 | 187.0 | 12155 | 1.5100 | 0.7427 |
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- | 0.7396 | 188.0 | 12220 | 1.5046 | 0.7388 |
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- | 0.7396 | 189.0 | 12285 | 1.5058 | 0.7407 |
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- | 0.7396 | 190.0 | 12350 | 1.5078 | 0.7368 |
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- | 0.7396 | 191.0 | 12415 | 1.5088 | 0.7427 |
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- | 0.7396 | 192.0 | 12480 | 1.5079 | 0.7407 |
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- | 0.7375 | 193.0 | 12545 | 1.5072 | 0.7446 |
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- | 0.7375 | 194.0 | 12610 | 1.5051 | 0.7446 |
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- | 0.7375 | 195.0 | 12675 | 1.5094 | 0.7388 |
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- | 0.7375 | 196.0 | 12740 | 1.5074 | 0.7427 |
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- | 0.7375 | 197.0 | 12805 | 1.5067 | 0.7427 |
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- | 0.7375 | 198.0 | 12870 | 1.5097 | 0.7388 |
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- | 0.7375 | 199.0 | 12935 | 1.5095 | 0.7388 |
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- | 0.7373 | 200.0 | 13000 | 1.5102 | 0.7388 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [Professor/Plant_Classification_model_vit-base-patch16-224-in21k](https://huggingface.co/Professor/Plant_Classification_model_vit-base-patch16-224-in21k) on the None dataset.
19
  It achieves the following results on the evaluation set:
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+ - Loss: 0.4976
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+ - Accuracy: 0.8737
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23
  ## Model description
24
 
 
44
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
  - lr_scheduler_type: linear
46
  - lr_scheduler_warmup_steps: 50
47
+ - num_epochs: 20
48
 
49
  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 193 | 1.6872 | 0.5531 |
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+ | No log | 2.0 | 386 | 1.2610 | 0.6490 |
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+ | 1.7011 | 3.0 | 579 | 1.1522 | 0.6658 |
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+ | 1.7011 | 4.0 | 772 | 0.9463 | 0.7293 |
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+ | 1.7011 | 5.0 | 965 | 0.8893 | 0.7377 |
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+ | 0.9968 | 6.0 | 1158 | 0.8774 | 0.7306 |
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+ | 0.9968 | 7.0 | 1351 | 0.7006 | 0.7908 |
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+ | 0.734 | 8.0 | 1544 | 0.7599 | 0.7791 |
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+ | 0.734 | 9.0 | 1737 | 0.6890 | 0.7895 |
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+ | 0.734 | 10.0 | 1930 | 0.6686 | 0.7882 |
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+ | 0.5624 | 11.0 | 2123 | 0.6111 | 0.8271 |
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+ | 0.5624 | 12.0 | 2316 | 0.6342 | 0.8122 |
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+ | 0.4342 | 13.0 | 2509 | 0.5493 | 0.8381 |
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+ | 0.4342 | 14.0 | 2702 | 0.5186 | 0.8452 |
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+ | 0.4342 | 15.0 | 2895 | 0.5610 | 0.8381 |
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+ | 0.3097 | 16.0 | 3088 | 0.5520 | 0.8439 |
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+ | 0.3097 | 17.0 | 3281 | 0.5237 | 0.8588 |
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+ | 0.3097 | 18.0 | 3474 | 0.4999 | 0.8659 |
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+ | 0.2119 | 19.0 | 3667 | 0.4976 | 0.8737 |
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+ | 0.2119 | 20.0 | 3860 | 0.5038 | 0.8711 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
model.safetensors CHANGED
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