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emotion_classification

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  1. README.md +65 -65
  2. model.safetensors +1 -1
  3. runs/Feb07_09-13-18_f75ff4190770/events.out.tfevents.1707297199.f75ff4190770.823.1 +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: google/vit-base-patch16-224-in21k
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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: 0.58125
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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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  # emotion_classification
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- This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1601
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- - Accuracy: 0.5813
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  ## Model description
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@@ -65,66 +65,66 @@ 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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- | 2.0632 | 1.0 | 40 | 2.0444 | 0.2437 |
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- | 2.0072 | 2.0 | 80 | 1.9824 | 0.375 |
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- | 1.9215 | 3.0 | 120 | 1.8844 | 0.4062 |
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- | 1.7969 | 4.0 | 160 | 1.7549 | 0.4688 |
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- | 1.6868 | 5.0 | 200 | 1.6343 | 0.4688 |
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- | 1.5946 | 6.0 | 240 | 1.5604 | 0.4938 |
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- | 1.5223 | 7.0 | 280 | 1.5055 | 0.525 |
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- | 1.4588 | 8.0 | 320 | 1.4665 | 0.5188 |
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- | 1.4157 | 9.0 | 360 | 1.3954 | 0.575 |
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- | 1.3713 | 10.0 | 400 | 1.3775 | 0.5312 |
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- | 1.3101 | 11.0 | 440 | 1.3572 | 0.5563 |
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- | 1.2881 | 12.0 | 480 | 1.3337 | 0.5437 |
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- | 1.2328 | 13.0 | 520 | 1.3253 | 0.525 |
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- | 1.2115 | 14.0 | 560 | 1.3186 | 0.5312 |
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- | 1.1531 | 15.0 | 600 | 1.3023 | 0.5375 |
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- | 1.1198 | 16.0 | 640 | 1.3149 | 0.5125 |
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- | 1.0833 | 17.0 | 680 | 1.2865 | 0.5312 |
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- | 1.0393 | 18.0 | 720 | 1.2498 | 0.525 |
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- | 1.0058 | 19.0 | 760 | 1.2166 | 0.5875 |
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- | 0.9721 | 20.0 | 800 | 1.1884 | 0.6 |
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- | 0.9387 | 21.0 | 840 | 1.1802 | 0.6 |
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- | 0.9505 | 22.0 | 880 | 1.2789 | 0.5125 |
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- | 0.8972 | 23.0 | 920 | 1.1719 | 0.5875 |
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- | 0.8665 | 24.0 | 960 | 1.2168 | 0.5625 |
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- | 0.8503 | 25.0 | 1000 | 1.1918 | 0.5437 |
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- | 0.8357 | 26.0 | 1040 | 1.2575 | 0.5062 |
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- | 0.8275 | 27.0 | 1080 | 1.1863 | 0.5938 |
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- | 0.7957 | 28.0 | 1120 | 1.2722 | 0.5375 |
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- | 0.8062 | 29.0 | 1160 | 1.1875 | 0.5687 |
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- | 0.7625 | 30.0 | 1200 | 1.2282 | 0.5625 |
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- | 0.7529 | 31.0 | 1240 | 1.1860 | 0.5687 |
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- | 0.721 | 32.0 | 1280 | 1.2366 | 0.55 |
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- | 0.7047 | 33.0 | 1320 | 1.1710 | 0.575 |
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- | 0.6803 | 34.0 | 1360 | 1.2395 | 0.5437 |
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- | 0.6858 | 35.0 | 1400 | 1.2439 | 0.5563 |
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- | 0.6613 | 36.0 | 1440 | 1.1809 | 0.5563 |
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- | 0.6453 | 37.0 | 1480 | 1.1892 | 0.5375 |
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- | 0.6052 | 38.0 | 1520 | 1.2089 | 0.5437 |
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- | 0.6193 | 39.0 | 1560 | 1.1421 | 0.5938 |
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- | 0.6026 | 40.0 | 1600 | 1.2163 | 0.5625 |
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- | 0.6345 | 41.0 | 1640 | 1.1429 | 0.5938 |
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- | 0.5842 | 42.0 | 1680 | 1.1989 | 0.5625 |
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- | 0.6326 | 43.0 | 1720 | 1.1958 | 0.6125 |
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- | 0.5933 | 44.0 | 1760 | 1.1793 | 0.5375 |
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- | 0.5902 | 45.0 | 1800 | 1.1795 | 0.5938 |
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- | 0.5497 | 46.0 | 1840 | 1.1797 | 0.5563 |
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- | 0.578 | 47.0 | 1880 | 1.1516 | 0.5813 |
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- | 0.5793 | 48.0 | 1920 | 1.1770 | 0.6 |
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- | 0.5857 | 49.0 | 1960 | 1.1991 | 0.5625 |
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- | 0.5742 | 50.0 | 2000 | 1.2873 | 0.5062 |
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- | 0.5696 | 51.0 | 2040 | 1.1254 | 0.6062 |
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- | 0.5745 | 52.0 | 2080 | 1.1817 | 0.6 |
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- | 0.5523 | 53.0 | 2120 | 1.2076 | 0.5875 |
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- | 0.5554 | 54.0 | 2160 | 1.1946 | 0.5938 |
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- | 0.5726 | 55.0 | 2200 | 1.1964 | 0.5813 |
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- | 0.5702 | 56.0 | 2240 | 1.1921 | 0.575 |
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- | 0.5396 | 57.0 | 2280 | 1.1801 | 0.6375 |
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- | 0.5444 | 58.0 | 2320 | 1.2866 | 0.5437 |
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- | 0.5713 | 59.0 | 2360 | 1.1860 | 0.5938 |
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- | 0.5626 | 60.0 | 2400 | 1.1601 | 0.5813 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: dennisjooo/emotion_classification
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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: 0.625
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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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  # emotion_classification
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+ This model is a fine-tuned version of [dennisjooo/emotion_classification](https://huggingface.co/dennisjooo/emotion_classification) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1505
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+ - Accuracy: 0.625
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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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+ | 0.6887 | 1.0 | 40 | 1.2010 | 0.55 |
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+ | 0.6532 | 2.0 | 80 | 1.1886 | 0.5875 |
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+ | 0.6007 | 3.0 | 120 | 1.0654 | 0.6562 |
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+ | 0.5773 | 4.0 | 160 | 1.1253 | 0.5938 |
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+ | 0.5632 | 5.0 | 200 | 1.1287 | 0.5687 |
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+ | 0.5642 | 6.0 | 240 | 1.1198 | 0.5938 |
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+ | 0.5136 | 7.0 | 280 | 1.2047 | 0.5625 |
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+ | 0.4931 | 8.0 | 320 | 1.1474 | 0.6 |
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+ | 0.4867 | 9.0 | 360 | 1.1146 | 0.6188 |
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+ | 0.4428 | 10.0 | 400 | 1.1561 | 0.6188 |
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+ | 0.4345 | 11.0 | 440 | 1.0993 | 0.6188 |
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+ | 0.4006 | 12.0 | 480 | 1.1786 | 0.5813 |
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+ | 0.4052 | 13.0 | 520 | 1.0929 | 0.6438 |
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+ | 0.4215 | 14.0 | 560 | 1.1574 | 0.6 |
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+ | 0.3702 | 15.0 | 600 | 1.2048 | 0.5625 |
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+ | 0.3692 | 16.0 | 640 | 1.2477 | 0.6 |
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+ | 0.3475 | 17.0 | 680 | 1.1999 | 0.5687 |
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+ | 0.3374 | 18.0 | 720 | 1.1560 | 0.6125 |
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+ | 0.3141 | 19.0 | 760 | 1.1571 | 0.5813 |
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+ | 0.2949 | 20.0 | 800 | 1.1420 | 0.6 |
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+ | 0.2972 | 21.0 | 840 | 1.2070 | 0.6 |
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+ | 0.317 | 22.0 | 880 | 1.2712 | 0.55 |
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+ | 0.2805 | 23.0 | 920 | 1.2785 | 0.5375 |
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+ | 0.2521 | 24.0 | 960 | 1.2000 | 0.575 |
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+ | 0.2951 | 25.0 | 1000 | 1.2287 | 0.5875 |
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+ | 0.2878 | 26.0 | 1040 | 1.3343 | 0.5625 |
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+ | 0.2564 | 27.0 | 1080 | 1.1686 | 0.5813 |
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+ | 0.2755 | 28.0 | 1120 | 1.3571 | 0.575 |
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+ | 0.3148 | 29.0 | 1160 | 1.3059 | 0.5563 |
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+ | 0.2942 | 30.0 | 1200 | 1.2678 | 0.5875 |
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+ | 0.2867 | 31.0 | 1240 | 1.2240 | 0.6062 |
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+ | 0.2489 | 32.0 | 1280 | 1.2434 | 0.5625 |
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+ | 0.2747 | 33.0 | 1320 | 1.1920 | 0.6312 |
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+ | 0.2279 | 34.0 | 1360 | 1.3587 | 0.5563 |
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+ | 0.2446 | 35.0 | 1400 | 1.2098 | 0.625 |
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+ | 0.1897 | 36.0 | 1440 | 1.1853 | 0.6375 |
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+ | 0.2076 | 37.0 | 1480 | 1.3183 | 0.6125 |
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+ | 0.2174 | 38.0 | 1520 | 1.2557 | 0.6312 |
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+ | 0.2297 | 39.0 | 1560 | 1.2031 | 0.6125 |
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+ | 0.2082 | 40.0 | 1600 | 1.2217 | 0.6188 |
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+ | 0.2457 | 41.0 | 1640 | 1.2759 | 0.6312 |
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+ | 0.2003 | 42.0 | 1680 | 1.2721 | 0.6188 |
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+ | 0.2394 | 43.0 | 1720 | 1.3591 | 0.5875 |
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+ | 0.2233 | 44.0 | 1760 | 1.2542 | 0.6375 |
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+ | 0.2181 | 45.0 | 1800 | 1.2548 | 0.6 |
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+ | 0.19 | 46.0 | 1840 | 1.1620 | 0.6188 |
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+ | 0.2213 | 47.0 | 1880 | 1.1367 | 0.6562 |
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+ | 0.211 | 48.0 | 1920 | 1.1482 | 0.6625 |
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+ | 0.2209 | 49.0 | 1960 | 1.2520 | 0.6188 |
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+ | 0.236 | 50.0 | 2000 | 1.3048 | 0.5813 |
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+ | 0.1973 | 51.0 | 2040 | 1.1874 | 0.6062 |
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+ | 0.2207 | 52.0 | 2080 | 1.2998 | 0.6125 |
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+ | 0.196 | 53.0 | 2120 | 1.2363 | 0.6188 |
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+ | 0.1915 | 54.0 | 2160 | 1.2635 | 0.625 |
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+ | 0.2543 | 55.0 | 2200 | 1.2311 | 0.6312 |
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+ | 0.2088 | 56.0 | 2240 | 1.2187 | 0.5875 |
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+ | 0.2018 | 57.0 | 2280 | 1.2326 | 0.5813 |
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+ | 0.1957 | 58.0 | 2320 | 1.3425 | 0.5875 |
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+ | 0.2228 | 59.0 | 2360 | 1.2038 | 0.6188 |
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+ | 0.1957 | 60.0 | 2400 | 1.1505 | 0.625 |
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  ### Framework versions
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