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Augusto777
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swiftformer-xs-ve-U13-b-80

Image Classification
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swiftformer
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  1. README.md +79 -98
  2. model.safetensors +1 -1
  3. runs/Jun12_16-44-11_DESKTOP-SKBE9FB/events.out.tfevents.1718232252.DESKTOP-SKBE9FB.1696.0 +2 -2
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8478260869565217
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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
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6640
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- - Accuracy: 0.8478
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  ## Model description
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@@ -51,7 +51,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -60,105 +60,86 @@ 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: 100
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  ### Training results
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67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 0.92 | 6 | 1.3858 | 0.2391 |
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- | 1.3856 | 2.0 | 13 | 1.3828 | 0.2826 |
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- | 1.3856 | 2.92 | 19 | 1.3769 | 0.1957 |
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- | 1.3734 | 4.0 | 26 | 1.3624 | 0.1304 |
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- | 1.2978 | 4.92 | 32 | 1.3553 | 0.1522 |
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- | 1.2978 | 6.0 | 39 | 1.4121 | 0.0870 |
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- | 1.1702 | 6.92 | 45 | 1.3720 | 0.2391 |
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- | 1.0743 | 8.0 | 52 | 1.3162 | 0.3478 |
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- | 1.0743 | 8.92 | 58 | 1.2252 | 0.3696 |
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- | 0.9504 | 10.0 | 65 | 1.1689 | 0.4348 |
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- | 0.8305 | 10.92 | 71 | 1.0516 | 0.5870 |
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- | 0.8305 | 12.0 | 78 | 0.9548 | 0.6739 |
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- | 0.7374 | 12.92 | 84 | 0.9138 | 0.7174 |
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- | 0.6207 | 14.0 | 91 | 0.9353 | 0.6522 |
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- | 0.6207 | 14.92 | 97 | 0.8640 | 0.6739 |
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- | 0.5184 | 16.0 | 104 | 0.8122 | 0.7826 |
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- | 0.4606 | 16.92 | 110 | 0.7136 | 0.8043 |
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- | 0.4606 | 18.0 | 117 | 0.7955 | 0.7609 |
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- | 0.4332 | 18.92 | 123 | 0.7790 | 0.6957 |
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- | 0.3315 | 20.0 | 130 | 0.8117 | 0.7391 |
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- | 0.3315 | 20.92 | 136 | 0.8068 | 0.7609 |
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- | 0.3229 | 22.0 | 143 | 0.8786 | 0.7826 |
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- | 0.3229 | 22.92 | 149 | 0.9030 | 0.7174 |
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- | 0.3065 | 24.0 | 156 | 0.8253 | 0.6522 |
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- | 0.2315 | 24.92 | 162 | 0.7398 | 0.8043 |
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- | 0.2315 | 26.0 | 169 | 0.7939 | 0.7609 |
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- | 0.222 | 26.92 | 175 | 0.6640 | 0.8478 |
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- | 0.1756 | 28.0 | 182 | 0.8510 | 0.7391 |
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- | 0.1756 | 28.92 | 188 | 0.9861 | 0.7174 |
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- | 0.1702 | 30.0 | 195 | 1.1060 | 0.7609 |
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- | 0.202 | 30.92 | 201 | 1.0929 | 0.7391 |
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- | 0.202 | 32.0 | 208 | 0.8670 | 0.7826 |
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- | 0.1665 | 32.92 | 214 | 0.8033 | 0.7609 |
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- | 0.1695 | 34.0 | 221 | 0.7235 | 0.7826 |
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- | 0.1695 | 34.92 | 227 | 0.8917 | 0.7609 |
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- | 0.1807 | 36.0 | 234 | 0.9215 | 0.7391 |
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- | 0.1289 | 36.92 | 240 | 0.8231 | 0.8043 |
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- | 0.1289 | 38.0 | 247 | 0.9256 | 0.7826 |
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- | 0.145 | 38.92 | 253 | 0.8866 | 0.7826 |
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- | 0.1422 | 40.0 | 260 | 0.8511 | 0.8261 |
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- | 0.1422 | 40.92 | 266 | 0.9956 | 0.7391 |
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- | 0.1313 | 42.0 | 273 | 1.3005 | 0.7391 |
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- | 0.1313 | 42.92 | 279 | 1.1532 | 0.6739 |
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- | 0.1128 | 44.0 | 286 | 1.0891 | 0.7391 |
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- | 0.1213 | 44.92 | 292 | 1.0765 | 0.7391 |
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- | 0.1213 | 46.0 | 299 | 0.9142 | 0.7391 |
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- | 0.1161 | 46.92 | 305 | 0.9100 | 0.7174 |
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- | 0.1123 | 48.0 | 312 | 0.8907 | 0.7826 |
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- | 0.1123 | 48.92 | 318 | 0.9462 | 0.7609 |
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- | 0.1107 | 50.0 | 325 | 0.8592 | 0.7391 |
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- | 0.0915 | 50.92 | 331 | 0.9894 | 0.7609 |
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- | 0.0915 | 52.0 | 338 | 1.1094 | 0.7609 |
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- | 0.0981 | 52.92 | 344 | 1.1956 | 0.7609 |
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- | 0.0762 | 54.0 | 351 | 1.0079 | 0.7826 |
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- | 0.0762 | 54.92 | 357 | 0.9899 | 0.7609 |
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- | 0.1083 | 56.0 | 364 | 0.9164 | 0.7826 |
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- | 0.1087 | 56.92 | 370 | 0.9263 | 0.7826 |
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- | 0.1087 | 58.0 | 377 | 0.9160 | 0.7391 |
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- | 0.0871 | 58.92 | 383 | 1.0179 | 0.7174 |
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- | 0.0852 | 60.0 | 390 | 0.9246 | 0.7391 |
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- | 0.0852 | 60.92 | 396 | 0.8929 | 0.8043 |
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- | 0.0613 | 62.0 | 403 | 0.9989 | 0.7174 |
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- | 0.0613 | 62.92 | 409 | 1.0367 | 0.7174 |
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- | 0.0899 | 64.0 | 416 | 1.1213 | 0.6957 |
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- | 0.0669 | 64.92 | 422 | 1.0093 | 0.7609 |
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- | 0.0669 | 66.0 | 429 | 1.0129 | 0.7391 |
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- | 0.0791 | 66.92 | 435 | 0.9979 | 0.7174 |
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- | 0.0848 | 68.0 | 442 | 1.0137 | 0.7391 |
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- | 0.0848 | 68.92 | 448 | 1.0761 | 0.6957 |
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- | 0.0799 | 70.0 | 455 | 1.0152 | 0.6957 |
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- | 0.0727 | 70.92 | 461 | 1.1302 | 0.6957 |
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- | 0.0727 | 72.0 | 468 | 1.0468 | 0.7174 |
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- | 0.0763 | 72.92 | 474 | 1.0759 | 0.6739 |
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- | 0.06 | 74.0 | 481 | 1.0803 | 0.7174 |
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- | 0.06 | 74.92 | 487 | 1.0484 | 0.6957 |
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- | 0.0746 | 76.0 | 494 | 0.9999 | 0.7174 |
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- | 0.0687 | 76.92 | 500 | 0.9937 | 0.7174 |
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- | 0.0687 | 78.0 | 507 | 1.1189 | 0.6957 |
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- | 0.0761 | 78.92 | 513 | 1.1013 | 0.6957 |
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- | 0.0729 | 80.0 | 520 | 1.0294 | 0.6957 |
149
- | 0.0729 | 80.92 | 526 | 1.0860 | 0.7174 |
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- | 0.0472 | 82.0 | 533 | 1.0327 | 0.7174 |
151
- | 0.0472 | 82.92 | 539 | 1.0225 | 0.7174 |
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- | 0.0519 | 84.0 | 546 | 1.1345 | 0.6957 |
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- | 0.0688 | 84.92 | 552 | 1.0923 | 0.6957 |
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- | 0.0688 | 86.0 | 559 | 1.0876 | 0.7174 |
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- | 0.0462 | 86.92 | 565 | 1.0740 | 0.6957 |
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- | 0.0457 | 88.0 | 572 | 1.1074 | 0.6957 |
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- | 0.0457 | 88.92 | 578 | 1.0777 | 0.6957 |
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- | 0.0482 | 90.0 | 585 | 1.0495 | 0.7391 |
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- | 0.0464 | 90.92 | 591 | 1.0395 | 0.7174 |
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- | 0.0464 | 92.0 | 598 | 1.1446 | 0.7174 |
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- | 0.0578 | 92.31 | 600 | 1.0596 | 0.6957 |
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  ### Framework versions
 
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
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+ value: 0.717391304347826
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  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
33
  It achieves the following results on the evaluation set:
34
+ - Loss: 0.7888
35
+ - Accuracy: 0.7174
36
 
37
  ## Model description
38
 
 
51
  ### Training hyperparameters
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53
  The following hyperparameters were used during training:
54
+ - learning_rate: 0.0002
55
  - train_batch_size: 32
56
  - eval_batch_size: 32
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  - seed: 42
 
60
  - 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: 80
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65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
+ | No log | 0.92 | 6 | 1.3859 | 0.2391 |
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+ | 1.3857 | 2.0 | 13 | 1.3834 | 0.2826 |
71
+ | 1.3857 | 2.92 | 19 | 1.3789 | 0.1957 |
72
+ | 1.3767 | 4.0 | 26 | 1.3666 | 0.1522 |
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+ | 1.3226 | 4.92 | 32 | 1.3565 | 0.1522 |
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+ | 1.3226 | 6.0 | 39 | 1.3902 | 0.1087 |
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+ | 1.1987 | 6.92 | 45 | 1.3712 | 0.2174 |
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+ | 1.1075 | 8.0 | 52 | 1.3197 | 0.3478 |
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+ | 1.1075 | 8.92 | 58 | 1.3649 | 0.3696 |
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+ | 0.9988 | 10.0 | 65 | 1.2583 | 0.3696 |
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+ | 0.8863 | 10.92 | 71 | 1.2484 | 0.3696 |
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+ | 0.8863 | 12.0 | 78 | 1.2869 | 0.4130 |
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+ | 0.8228 | 12.92 | 84 | 1.1678 | 0.4783 |
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+ | 0.7456 | 14.0 | 91 | 1.0275 | 0.6739 |
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+ | 0.7456 | 14.92 | 97 | 0.9702 | 0.7174 |
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+ | 0.6595 | 16.0 | 104 | 0.9103 | 0.6957 |
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+ | 0.5995 | 16.92 | 110 | 0.8506 | 0.7391 |
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+ | 0.5995 | 18.0 | 117 | 0.8514 | 0.7174 |
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+ | 0.5826 | 18.92 | 123 | 0.8964 | 0.7391 |
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+ | 0.4818 | 20.0 | 130 | 0.8550 | 0.7609 |
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+ | 0.4818 | 20.92 | 136 | 0.7132 | 0.8261 |
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+ | 0.4553 | 22.0 | 143 | 0.6973 | 0.7826 |
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+ | 0.4553 | 22.92 | 149 | 0.7496 | 0.7391 |
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+ | 0.4276 | 24.0 | 156 | 0.9087 | 0.6957 |
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+ | 0.3375 | 24.92 | 162 | 0.7787 | 0.8261 |
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+ | 0.3375 | 26.0 | 169 | 0.7132 | 0.8043 |
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+ | 0.3199 | 26.92 | 175 | 0.7570 | 0.7391 |
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+ | 0.2756 | 28.0 | 182 | 0.7873 | 0.6957 |
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+ | 0.2756 | 28.92 | 188 | 0.7895 | 0.7609 |
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+ | 0.2254 | 30.0 | 195 | 0.7443 | 0.8043 |
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+ | 0.2576 | 30.92 | 201 | 0.9623 | 0.6739 |
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+ | 0.2576 | 32.0 | 208 | 0.7349 | 0.7826 |
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+ | 0.2113 | 32.92 | 214 | 0.7887 | 0.7609 |
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+ | 0.1978 | 34.0 | 221 | 0.8921 | 0.7391 |
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+ | 0.1978 | 34.92 | 227 | 0.8102 | 0.7391 |
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+ | 0.2455 | 36.0 | 234 | 0.8947 | 0.7391 |
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+ | 0.1809 | 36.92 | 240 | 0.8144 | 0.7826 |
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+ | 0.1809 | 38.0 | 247 | 0.8290 | 0.7174 |
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+ | 0.1967 | 38.92 | 253 | 0.8135 | 0.7391 |
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+ | 0.1608 | 40.0 | 260 | 0.8065 | 0.7609 |
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+ | 0.1608 | 40.92 | 266 | 0.7399 | 0.7609 |
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+ | 0.1704 | 42.0 | 273 | 0.7099 | 0.8043 |
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+ | 0.1704 | 42.92 | 279 | 0.7569 | 0.7826 |
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+ | 0.1682 | 44.0 | 286 | 0.8459 | 0.7826 |
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+ | 0.1607 | 44.92 | 292 | 0.7311 | 0.7609 |
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+ | 0.1607 | 46.0 | 299 | 0.7833 | 0.7174 |
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+ | 0.1589 | 46.92 | 305 | 0.8073 | 0.6957 |
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+ | 0.1524 | 48.0 | 312 | 0.7473 | 0.7609 |
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+ | 0.1524 | 48.92 | 318 | 0.6780 | 0.8043 |
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+ | 0.1586 | 50.0 | 325 | 0.7573 | 0.7174 |
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+ | 0.128 | 50.92 | 331 | 0.7614 | 0.7391 |
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+ | 0.128 | 52.0 | 338 | 0.7338 | 0.7609 |
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+ | 0.1254 | 52.92 | 344 | 0.7666 | 0.7391 |
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+ | 0.1206 | 54.0 | 351 | 0.8433 | 0.7174 |
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+ | 0.1206 | 54.92 | 357 | 0.8747 | 0.6957 |
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+ | 0.1398 | 56.0 | 364 | 0.8940 | 0.7174 |
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+ | 0.1536 | 56.92 | 370 | 0.7781 | 0.7826 |
126
+ | 0.1536 | 58.0 | 377 | 0.7351 | 0.7391 |
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+ | 0.1281 | 58.92 | 383 | 0.7601 | 0.7174 |
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+ | 0.1156 | 60.0 | 390 | 0.7991 | 0.7174 |
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+ | 0.1156 | 60.92 | 396 | 0.7776 | 0.7609 |
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+ | 0.0852 | 62.0 | 403 | 0.7838 | 0.7391 |
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+ | 0.0852 | 62.92 | 409 | 0.7752 | 0.7609 |
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+ | 0.1106 | 64.0 | 416 | 0.7541 | 0.7609 |
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+ | 0.0817 | 64.92 | 422 | 0.7536 | 0.7391 |
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+ | 0.0817 | 66.0 | 429 | 0.8129 | 0.7609 |
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+ | 0.1211 | 66.92 | 435 | 0.7884 | 0.7609 |
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+ | 0.0944 | 68.0 | 442 | 0.8011 | 0.7609 |
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+ | 0.0944 | 68.92 | 448 | 0.8068 | 0.7391 |
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+ | 0.1187 | 70.0 | 455 | 0.7796 | 0.7391 |
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+ | 0.0935 | 70.92 | 461 | 0.7934 | 0.7391 |
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+ | 0.0935 | 72.0 | 468 | 0.7367 | 0.7391 |
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+ | 0.109 | 72.92 | 474 | 0.7515 | 0.7391 |
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+ | 0.1006 | 73.85 | 480 | 0.7888 | 0.7174 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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