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hkivancoral
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hushem_1x_deit_base_adamax_001_fold1

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  1. README.md +53 -53
  2. model.safetensors +1 -1
  3. runs/Nov15_13-15-14_2fc4888c5945/events.out.tfevents.1700054122.2fc4888c5945.935.0 +2 -2
README.md CHANGED
@@ -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: 0.5111111111111111
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 4.3407
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- - Accuracy: 0.5111
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  ## Model description
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@@ -65,56 +65,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 6 | 1.5090 | 0.2444 |
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- | 1.7013 | 2.0 | 12 | 1.3998 | 0.2667 |
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- | 1.7013 | 3.0 | 18 | 1.3736 | 0.3778 |
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- | 1.3804 | 4.0 | 24 | 2.2697 | 0.2444 |
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- | 1.2948 | 5.0 | 30 | 1.3181 | 0.3556 |
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- | 1.2948 | 6.0 | 36 | 1.4857 | 0.3111 |
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- | 1.1726 | 7.0 | 42 | 1.2439 | 0.3778 |
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- | 1.1726 | 8.0 | 48 | 1.5434 | 0.4 |
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- | 1.1199 | 9.0 | 54 | 1.5452 | 0.3556 |
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- | 0.9306 | 10.0 | 60 | 1.8843 | 0.3111 |
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- | 0.9306 | 11.0 | 66 | 1.7110 | 0.4889 |
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- | 0.8594 | 12.0 | 72 | 2.3007 | 0.4444 |
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- | 0.8594 | 13.0 | 78 | 2.2030 | 0.4 |
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- | 0.6332 | 14.0 | 84 | 2.6779 | 0.3778 |
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- | 0.6799 | 15.0 | 90 | 1.9397 | 0.4 |
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- | 0.6799 | 16.0 | 96 | 1.7641 | 0.4 |
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- | 0.4959 | 17.0 | 102 | 2.2034 | 0.4 |
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- | 0.4959 | 18.0 | 108 | 2.6569 | 0.3556 |
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- | 0.302 | 19.0 | 114 | 2.6259 | 0.4222 |
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- | 0.1746 | 20.0 | 120 | 2.6945 | 0.4889 |
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- | 0.1746 | 21.0 | 126 | 3.0869 | 0.4222 |
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- | 0.1138 | 22.0 | 132 | 2.6734 | 0.4667 |
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- | 0.1138 | 23.0 | 138 | 3.4608 | 0.4 |
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- | 0.0701 | 24.0 | 144 | 2.8698 | 0.5111 |
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- | 0.1001 | 25.0 | 150 | 3.7040 | 0.4222 |
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- | 0.1001 | 26.0 | 156 | 4.1291 | 0.4 |
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- | 0.1061 | 27.0 | 162 | 2.9920 | 0.5333 |
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- | 0.1061 | 28.0 | 168 | 4.6762 | 0.4222 |
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- | 0.05 | 29.0 | 174 | 3.9112 | 0.4889 |
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- | 0.0229 | 30.0 | 180 | 4.1548 | 0.4667 |
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- | 0.0229 | 31.0 | 186 | 4.2153 | 0.4889 |
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- | 0.0009 | 32.0 | 192 | 4.2545 | 0.4889 |
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- | 0.0009 | 33.0 | 198 | 4.2657 | 0.4889 |
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- | 0.0003 | 34.0 | 204 | 4.2768 | 0.5111 |
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- | 0.0003 | 35.0 | 210 | 4.2900 | 0.5111 |
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- | 0.0003 | 36.0 | 216 | 4.3028 | 0.5111 |
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- | 0.0003 | 37.0 | 222 | 4.3145 | 0.5111 |
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- | 0.0003 | 38.0 | 228 | 4.3255 | 0.5111 |
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- | 0.0002 | 39.0 | 234 | 4.3333 | 0.5111 |
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- | 0.0002 | 40.0 | 240 | 4.3377 | 0.5111 |
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- | 0.0002 | 41.0 | 246 | 4.3402 | 0.5111 |
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- | 0.0002 | 42.0 | 252 | 4.3407 | 0.5111 |
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- | 0.0002 | 43.0 | 258 | 4.3407 | 0.5111 |
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- | 0.0002 | 44.0 | 264 | 4.3407 | 0.5111 |
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- | 0.0002 | 45.0 | 270 | 4.3407 | 0.5111 |
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- | 0.0002 | 46.0 | 276 | 4.3407 | 0.5111 |
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- | 0.0002 | 47.0 | 282 | 4.3407 | 0.5111 |
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- | 0.0002 | 48.0 | 288 | 4.3407 | 0.5111 |
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- | 0.0002 | 49.0 | 294 | 4.3407 | 0.5111 |
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- | 0.0002 | 50.0 | 300 | 4.3407 | 0.5111 |
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  ### Framework versions
 
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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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  ---
27
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
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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: 4.0186
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+ - Accuracy: 0.5333
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 6 | 1.5701 | 0.2444 |
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+ | 1.7784 | 2.0 | 12 | 1.4475 | 0.2444 |
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+ | 1.7784 | 3.0 | 18 | 1.5245 | 0.2444 |
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+ | 1.3959 | 4.0 | 24 | 1.4708 | 0.4222 |
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+ | 1.2593 | 5.0 | 30 | 1.4970 | 0.2889 |
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+ | 1.2593 | 6.0 | 36 | 2.3855 | 0.2444 |
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+ | 1.1884 | 7.0 | 42 | 1.0899 | 0.5333 |
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+ | 1.1884 | 8.0 | 48 | 1.5303 | 0.3778 |
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+ | 1.0528 | 9.0 | 54 | 1.8879 | 0.2667 |
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+ | 0.9521 | 10.0 | 60 | 1.5051 | 0.3556 |
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+ | 0.9521 | 11.0 | 66 | 1.7383 | 0.4222 |
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+ | 0.832 | 12.0 | 72 | 1.4982 | 0.4667 |
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+ | 0.832 | 13.0 | 78 | 2.2428 | 0.4222 |
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+ | 0.6131 | 14.0 | 84 | 2.0924 | 0.4667 |
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+ | 0.7375 | 15.0 | 90 | 1.9680 | 0.3778 |
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+ | 0.7375 | 16.0 | 96 | 2.1272 | 0.4 |
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+ | 0.3749 | 17.0 | 102 | 2.6064 | 0.4222 |
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+ | 0.3749 | 18.0 | 108 | 3.2946 | 0.4 |
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+ | 0.1952 | 19.0 | 114 | 3.4322 | 0.4 |
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+ | 0.1436 | 20.0 | 120 | 3.6588 | 0.4222 |
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+ | 0.1436 | 21.0 | 126 | 2.5255 | 0.4889 |
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+ | 0.198 | 22.0 | 132 | 4.0901 | 0.3778 |
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+ | 0.198 | 23.0 | 138 | 3.7265 | 0.4444 |
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+ | 0.1826 | 24.0 | 144 | 2.5207 | 0.5333 |
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+ | 0.0757 | 25.0 | 150 | 3.1947 | 0.4667 |
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+ | 0.0757 | 26.0 | 156 | 2.8055 | 0.5333 |
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+ | 0.0579 | 27.0 | 162 | 2.7690 | 0.5333 |
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+ | 0.0579 | 28.0 | 168 | 3.0584 | 0.5333 |
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+ | 0.0219 | 29.0 | 174 | 2.7699 | 0.6 |
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+ | 0.0037 | 30.0 | 180 | 3.6076 | 0.5556 |
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+ | 0.0037 | 31.0 | 186 | 4.1981 | 0.4667 |
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+ | 0.0005 | 32.0 | 192 | 4.2123 | 0.5111 |
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+ | 0.0005 | 33.0 | 198 | 4.1138 | 0.4889 |
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+ | 0.0004 | 34.0 | 204 | 4.0577 | 0.5333 |
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+ | 0.0002 | 35.0 | 210 | 4.0352 | 0.5333 |
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+ | 0.0002 | 36.0 | 216 | 4.0255 | 0.5333 |
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+ | 0.0002 | 37.0 | 222 | 4.0206 | 0.5333 |
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+ | 0.0002 | 38.0 | 228 | 4.0191 | 0.5333 |
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+ | 0.0001 | 39.0 | 234 | 4.0188 | 0.5333 |
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+ | 0.0001 | 40.0 | 240 | 4.0186 | 0.5333 |
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+ | 0.0001 | 41.0 | 246 | 4.0185 | 0.5333 |
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+ | 0.0001 | 42.0 | 252 | 4.0186 | 0.5333 |
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+ | 0.0001 | 43.0 | 258 | 4.0186 | 0.5333 |
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+ | 0.0001 | 44.0 | 264 | 4.0186 | 0.5333 |
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+ | 0.0001 | 45.0 | 270 | 4.0186 | 0.5333 |
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+ | 0.0001 | 46.0 | 276 | 4.0186 | 0.5333 |
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+ | 0.0001 | 47.0 | 282 | 4.0186 | 0.5333 |
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+ | 0.0001 | 48.0 | 288 | 4.0186 | 0.5333 |
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+ | 0.0001 | 49.0 | 294 | 4.0186 | 0.5333 |
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+ | 0.0001 | 50.0 | 300 | 4.0186 | 0.5333 |
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  ### Framework versions
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