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queue_detection

Object Detection
Transformers
Safetensors
conditional_detr
Generated from Trainer
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queue_detection

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  1. README.md +46 -46
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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- base_model: microsoft/conditional-detr-resnet-50
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -15,23 +15,23 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4822
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- - Map: 0.2108
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- - Map 50: 0.3072
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- - Map 75: 0.2725
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  - Map Small: -1.0
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- - Map Medium: -1.0
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- - Map Large: 0.2219
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- - Mar 1: 0.1833
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- - Mar 10: 0.4195
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- - Mar 100: 0.736
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  - Mar Small: -1.0
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- - Mar Medium: -1.0
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- - Mar Large: 0.736
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- - Map Cashier: 0.0544
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- - Mar 100 Cashier: 0.8053
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- - Map Cx: 0.3672
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- - Mar 100 Cx: 0.6667
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  ## Model description
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@@ -63,36 +63,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Cashier | Mar 100 Cashier | Map Cx | Mar 100 Cx |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-----------:|:---------------:|:------:|:----------:|
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- | No log | 1.0 | 5 | 38.9601 | 0.0007 | 0.0042 | 0.0 | -1.0 | -1.0 | 0.001 | 0.0 | 0.0186 | 0.053 | -1.0 | -1.0 | 0.053 | 0.0004 | 0.0526 | 0.001 | 0.0533 |
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- | No log | 2.0 | 10 | 20.3884 | 0.0053 | 0.0378 | 0.001 | -1.0 | -1.0 | 0.0119 | 0.0 | 0.0133 | 0.11 | -1.0 | -1.0 | 0.11 | 0.0 | 0.0 | 0.0106 | 0.22 |
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- | No log | 3.0 | 15 | 8.6229 | 0.0257 | 0.0582 | 0.0072 | -1.0 | -1.0 | 0.0573 | 0.0333 | 0.12 | 0.1737 | -1.0 | -1.0 | 0.1737 | 0.0002 | 0.0474 | 0.0512 | 0.3 |
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- | No log | 4.0 | 20 | 5.4986 | 0.0061 | 0.02 | 0.0018 | -1.0 | -1.0 | 0.0175 | 0.0 | 0.0833 | 0.1 | -1.0 | -1.0 | 0.1 | 0.0 | 0.0 | 0.0122 | 0.2 |
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- | No log | 5.0 | 25 | 3.2810 | 0.0152 | 0.0644 | 0.0 | -1.0 | -1.0 | 0.0182 | 0.0067 | 0.0933 | 0.1989 | -1.0 | -1.0 | 0.1989 | 0.004 | 0.1579 | 0.0264 | 0.24 |
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- | No log | 6.0 | 30 | 2.4527 | 0.0174 | 0.0707 | 0.0008 | -1.0 | -1.0 | 0.0201 | 0.0067 | 0.0667 | 0.3286 | -1.0 | -1.0 | 0.3286 | 0.0076 | 0.3105 | 0.0272 | 0.3467 |
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- | No log | 7.0 | 35 | 2.1059 | 0.0222 | 0.0715 | 0.0077 | -1.0 | 0.0 | 0.0244 | 0.0233 | 0.0993 | 0.4733 | -1.0 | 0.0 | 0.4857 | 0.017 | 0.6 | 0.0273 | 0.3467 |
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- | No log | 8.0 | 40 | 2.1013 | 0.035 | 0.117 | 0.0054 | -1.0 | -1.0 | 0.0354 | 0.0333 | 0.0467 | 0.3653 | -1.0 | -1.0 | 0.3653 | 0.0204 | 0.6105 | 0.0497 | 0.12 |
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- | No log | 9.0 | 45 | 1.9401 | 0.0412 | 0.1081 | 0.0058 | -1.0 | -1.0 | 0.042 | 0.0267 | 0.04 | 0.3639 | -1.0 | -1.0 | 0.3639 | 0.0184 | 0.6211 | 0.064 | 0.1067 |
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- | No log | 10.0 | 50 | 2.2227 | 0.0071 | 0.0254 | 0.0017 | -1.0 | -1.0 | 0.0075 | 0.0 | 0.0433 | 0.256 | -1.0 | -1.0 | 0.256 | 0.0044 | 0.3053 | 0.0098 | 0.2067 |
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- | No log | 11.0 | 55 | 1.9404 | 0.0126 | 0.033 | 0.01 | -1.0 | -1.0 | 0.0127 | 0.0 | 0.08 | 0.333 | -1.0 | -1.0 | 0.333 | 0.0082 | 0.4526 | 0.0169 | 0.2133 |
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- | No log | 12.0 | 60 | 1.8410 | 0.0186 | 0.0658 | 0.0078 | -1.0 | -1.0 | 0.0187 | 0.0 | 0.0733 | 0.3591 | -1.0 | -1.0 | 0.3591 | 0.0125 | 0.5316 | 0.0247 | 0.1867 |
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- | No log | 13.0 | 65 | 1.7476 | 0.0735 | 0.1829 | 0.0136 | -1.0 | -1.0 | 0.0736 | 0.0633 | 0.1133 | 0.4335 | -1.0 | -1.0 | 0.4335 | 0.0105 | 0.4737 | 0.1366 | 0.3933 |
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- | No log | 14.0 | 70 | 1.8939 | 0.0634 | 0.1492 | 0.0276 | -1.0 | -1.0 | 0.0638 | 0.05 | 0.2033 | 0.3719 | -1.0 | -1.0 | 0.3719 | 0.0032 | 0.2105 | 0.1236 | 0.5333 |
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- | No log | 15.0 | 75 | 1.7653 | 0.0535 | 0.1438 | 0.0387 | -1.0 | -1.0 | 0.0554 | 0.0964 | 0.1929 | 0.4917 | -1.0 | -1.0 | 0.4917 | 0.0103 | 0.4263 | 0.0968 | 0.5571 |
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- | No log | 16.0 | 80 | 1.6493 | 0.0988 | 0.2205 | 0.0787 | -1.0 | -1.0 | 0.1014 | 0.0733 | 0.2419 | 0.6505 | -1.0 | -1.0 | 0.6505 | 0.0225 | 0.7211 | 0.1751 | 0.58 |
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- | No log | 17.0 | 85 | 1.7624 | 0.1198 | 0.2464 | 0.0858 | 0.0 | -1.0 | 0.1289 | 0.1167 | 0.2333 | 0.6149 | 0.0 | -1.0 | 0.6352 | 0.0285 | 0.6632 | 0.211 | 0.5667 |
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- | No log | 18.0 | 90 | 1.8609 | 0.149 | 0.3181 | 0.0874 | -1.0 | -1.0 | 0.1517 | 0.13 | 0.2861 | 0.5789 | -1.0 | -1.0 | 0.5789 | 0.0403 | 0.6579 | 0.2576 | 0.5 |
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- | No log | 19.0 | 95 | 1.6860 | 0.1455 | 0.257 | 0.1026 | -1.0 | -1.0 | 0.1497 | 0.1393 | 0.2697 | 0.6496 | -1.0 | -1.0 | 0.6496 | 0.039 | 0.7421 | 0.2521 | 0.5571 |
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- | No log | 20.0 | 100 | 1.7541 | 0.1966 | 0.3274 | 0.2313 | -1.0 | -1.0 | 0.1994 | 0.17 | 0.317 | 0.6182 | -1.0 | -1.0 | 0.6182 | 0.0379 | 0.6632 | 0.3553 | 0.5733 |
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- | No log | 21.0 | 105 | 1.7043 | 0.1735 | 0.2572 | 0.1786 | -1.0 | 0.0 | 0.1913 | 0.1821 | 0.3295 | 0.6252 | -1.0 | 0.0 | 0.6472 | 0.0459 | 0.6789 | 0.3012 | 0.5714 |
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- | No log | 22.0 | 110 | 1.5489 | 0.1959 | 0.3051 | 0.264 | -1.0 | -1.0 | 0.2039 | 0.17 | 0.3568 | 0.6896 | -1.0 | -1.0 | 0.6896 | 0.046 | 0.7526 | 0.3458 | 0.6267 |
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- | No log | 23.0 | 115 | 1.6402 | 0.166 | 0.293 | 0.1791 | -1.0 | -1.0 | 0.1773 | 0.1432 | 0.2851 | 0.6496 | -1.0 | -1.0 | 0.6496 | 0.048 | 0.7526 | 0.284 | 0.5467 |
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- | No log | 24.0 | 120 | 1.5800 | 0.188 | 0.3099 | 0.1815 | -1.0 | -1.0 | 0.1965 | 0.1791 | 0.3337 | 0.693 | -1.0 | -1.0 | 0.693 | 0.0408 | 0.7526 | 0.3352 | 0.6333 |
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- | No log | 25.0 | 125 | 1.5566 | 0.1921 | 0.3038 | 0.2227 | -1.0 | -1.0 | 0.2037 | 0.17 | 0.4244 | 0.6928 | -1.0 | -1.0 | 0.6928 | 0.0642 | 0.7789 | 0.32 | 0.6067 |
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- | No log | 26.0 | 130 | 1.7227 | 0.2044 | 0.3337 | 0.2155 | -1.0 | -1.0 | 0.2145 | 0.1667 | 0.3319 | 0.5968 | -1.0 | -1.0 | 0.5968 | 0.0484 | 0.6737 | 0.3604 | 0.52 |
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- | No log | 27.0 | 135 | 1.5184 | 0.2095 | 0.3161 | 0.2389 | -1.0 | -1.0 | 0.2211 | 0.1877 | 0.3163 | 0.7026 | -1.0 | -1.0 | 0.7026 | 0.0603 | 0.8053 | 0.3586 | 0.6 |
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- | No log | 28.0 | 140 | 1.5156 | 0.2172 | 0.3273 | 0.2672 | -1.0 | -1.0 | 0.2286 | 0.2077 | 0.4402 | 0.7226 | -1.0 | -1.0 | 0.7226 | 0.0681 | 0.8053 | 0.3664 | 0.64 |
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- | No log | 29.0 | 145 | 1.6211 | 0.1652 | 0.2652 | 0.2007 | -1.0 | -1.0 | 0.1737 | 0.15 | 0.4081 | 0.677 | -1.0 | -1.0 | 0.677 | 0.0463 | 0.7474 | 0.2841 | 0.6067 |
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- | No log | 30.0 | 150 | 1.4822 | 0.2108 | 0.3072 | 0.2725 | -1.0 | -1.0 | 0.2219 | 0.1833 | 0.4195 | 0.736 | -1.0 | -1.0 | 0.736 | 0.0544 | 0.8053 | 0.3672 | 0.6667 |
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  ### Framework versions
 
1
  ---
 
2
  license: apache-2.0
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+ base_model: microsoft/conditional-detr-resnet-50
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  tags:
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  - generated_from_trainer
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  model-index:
 
15
 
16
  This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2068
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+ - Map: 0.9189
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+ - Map 50: 0.9898
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+ - Map 75: 0.9755
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  - Map Small: -1.0
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+ - Map Medium: 0.1871
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+ - Map Large: 0.9234
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+ - Mar 1: 0.49
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+ - Mar 10: 0.9447
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+ - Mar 100: 0.9466
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  - Mar Small: -1.0
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+ - Mar Medium: 0.2615
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+ - Mar Large: 0.9505
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+ - Map Cashier: 0.935
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+ - Mar 100 Cashier: 0.9592
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+ - Map Cx: 0.9027
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+ - Mar 100 Cx: 0.9341
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Cashier | Mar 100 Cashier | Map Cx | Mar 100 Cx |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-----------:|:---------------:|:------:|:----------:|
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+ | No log | 1.0 | 218 | 1.3811 | 0.2363 | 0.4099 | 0.2515 | -1.0 | 0.0 | 0.2376 | 0.2364 | 0.5459 | 0.719 | -1.0 | 0.0 | 0.7238 | 0.2986 | 0.7856 | 0.174 | 0.6523 |
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+ | No log | 2.0 | 436 | 0.9194 | 0.575 | 0.8212 | 0.6661 | -1.0 | 0.038 | 0.5796 | 0.3518 | 0.7412 | 0.7921 | -1.0 | 0.1 | 0.7978 | 0.6716 | 0.8368 | 0.4783 | 0.7473 |
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+ | 2.4678 | 3.0 | 654 | 0.6968 | 0.6863 | 0.9358 | 0.8313 | -1.0 | 0.0679 | 0.6906 | 0.3901 | 0.7636 | 0.7806 | -1.0 | 0.12 | 0.7848 | 0.7373 | 0.8132 | 0.6354 | 0.7481 |
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+ | 2.4678 | 4.0 | 872 | 0.6535 | 0.7043 | 0.9566 | 0.8452 | -1.0 | 0.0421 | 0.7091 | 0.3916 | 0.7748 | 0.7871 | -1.0 | 0.1615 | 0.7909 | 0.772 | 0.8416 | 0.6366 | 0.7326 |
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+ | 0.723 | 5.0 | 1090 | 0.5906 | 0.7447 | 0.9667 | 0.8788 | -1.0 | 0.0367 | 0.7494 | 0.4113 | 0.8026 | 0.8122 | -1.0 | 0.0955 | 0.8166 | 0.7913 | 0.8551 | 0.6981 | 0.7693 |
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+ | 0.723 | 6.0 | 1308 | 0.5508 | 0.7473 | 0.9631 | 0.893 | 0.0 | 0.0672 | 0.7527 | 0.4199 | 0.8021 | 0.8067 | 0.0 | 0.1077 | 0.812 | 0.7943 | 0.8428 | 0.7002 | 0.7705 |
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+ | 0.5955 | 7.0 | 1526 | 0.5073 | 0.7626 | 0.9656 | 0.9062 | -1.0 | 0.0515 | 0.7673 | 0.423 | 0.8156 | 0.8182 | -1.0 | 0.2273 | 0.8226 | 0.7917 | 0.8476 | 0.7335 | 0.7887 |
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+ | 0.5955 | 8.0 | 1744 | 0.5195 | 0.7452 | 0.9721 | 0.8832 | -1.0 | 0.0559 | 0.7511 | 0.417 | 0.8022 | 0.8105 | -1.0 | 0.1607 | 0.8149 | 0.7925 | 0.8448 | 0.6979 | 0.7762 |
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+ | 0.5955 | 9.0 | 1962 | 0.4328 | 0.8028 | 0.9786 | 0.938 | -1.0 | 0.0481 | 0.808 | 0.441 | 0.8515 | 0.8573 | -1.0 | 0.1154 | 0.8625 | 0.8348 | 0.8846 | 0.7708 | 0.8299 |
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+ | 0.5055 | 10.0 | 2180 | 0.4195 | 0.8085 | 0.9847 | 0.944 | 0.0 | 0.0616 | 0.8129 | 0.4365 | 0.8526 | 0.8591 | 0.0 | 0.1111 | 0.8635 | 0.8241 | 0.8793 | 0.7929 | 0.839 |
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+ | 0.5055 | 11.0 | 2398 | 0.4155 | 0.8145 | 0.9803 | 0.9465 | 0.0 | 0.0555 | 0.8236 | 0.4455 | 0.8556 | 0.8598 | 0.0 | 0.1 | 0.8691 | 0.8373 | 0.8813 | 0.7918 | 0.8383 |
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+ | 0.457 | 12.0 | 2616 | 0.3886 | 0.8301 | 0.984 | 0.9549 | 0.0 | 0.1278 | 0.8355 | 0.4513 | 0.8691 | 0.8731 | 0.0 | 0.1625 | 0.878 | 0.8596 | 0.9024 | 0.8006 | 0.8438 |
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+ | 0.457 | 13.0 | 2834 | 0.3750 | 0.829 | 0.9878 | 0.9563 | -1.0 | 0.1024 | 0.8333 | 0.4508 | 0.8692 | 0.8735 | -1.0 | 0.17 | 0.8772 | 0.8507 | 0.894 | 0.8073 | 0.8531 |
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+ | 0.3971 | 14.0 | 3052 | 0.3571 | 0.8427 | 0.9871 | 0.9524 | -1.0 | 0.0895 | 0.849 | 0.4576 | 0.8803 | 0.8843 | -1.0 | 0.1531 | 0.8903 | 0.8627 | 0.9071 | 0.8227 | 0.8615 |
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+ | 0.3971 | 15.0 | 3270 | 0.3637 | 0.8398 | 0.983 | 0.9587 | 0.0 | 0.0682 | 0.8481 | 0.4565 | 0.8754 | 0.8779 | 0.0 | 0.0972 | 0.8867 | 0.8692 | 0.9062 | 0.8104 | 0.8496 |
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+ | 0.3971 | 16.0 | 3488 | 0.3373 | 0.8494 | 0.9894 | 0.9514 | -1.0 | 0.2611 | 0.8534 | 0.4653 | 0.8849 | 0.8883 | -1.0 | 0.3929 | 0.8923 | 0.8756 | 0.9121 | 0.8233 | 0.8645 |
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+ | 0.387 | 17.0 | 3706 | 0.2885 | 0.8744 | 0.9895 | 0.9712 | -1.0 | 0.1702 | 0.8786 | 0.472 | 0.9076 | 0.9083 | -1.0 | 0.2269 | 0.9124 | 0.8951 | 0.927 | 0.8537 | 0.8897 |
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+ | 0.387 | 18.0 | 3924 | 0.2835 | 0.8737 | 0.9893 | 0.9742 | -1.0 | 0.1473 | 0.8773 | 0.4732 | 0.9064 | 0.9085 | -1.0 | 0.1833 | 0.9119 | 0.8977 | 0.9287 | 0.8498 | 0.8883 |
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+ | 0.3216 | 19.0 | 4142 | 0.2699 | 0.8816 | 0.9894 | 0.9722 | -1.0 | 0.1445 | 0.8865 | 0.4786 | 0.9123 | 0.9142 | -1.0 | 0.3286 | 0.9192 | 0.9065 | 0.9364 | 0.8568 | 0.8919 |
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+ | 0.3216 | 20.0 | 4360 | 0.2711 | 0.8813 | 0.9895 | 0.9727 | -1.0 | 0.1181 | 0.8858 | 0.4775 | 0.914 | 0.9156 | -1.0 | 0.1917 | 0.9199 | 0.9041 | 0.9348 | 0.8584 | 0.8963 |
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+ | 0.3117 | 21.0 | 4578 | 0.2489 | 0.8889 | 0.9897 | 0.9763 | -1.0 | 0.2022 | 0.8934 | 0.4817 | 0.9215 | 0.9228 | -1.0 | 0.25 | 0.9261 | 0.911 | 0.9415 | 0.8668 | 0.9041 |
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+ | 0.3117 | 22.0 | 4796 | 0.2739 | 0.8854 | 0.9846 | 0.9685 | 0.0 | 0.1351 | 0.8944 | 0.4797 | 0.9132 | 0.9159 | 0.0 | 0.2059 | 0.9244 | 0.9071 | 0.9351 | 0.8638 | 0.8968 |
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+ | 0.2812 | 23.0 | 5014 | 0.2489 | 0.8989 | 0.9895 | 0.9702 | -1.0 | 0.188 | 0.9023 | 0.482 | 0.9246 | 0.9269 | -1.0 | 0.2536 | 0.9309 | 0.9183 | 0.9419 | 0.8795 | 0.9118 |
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+ | 0.2812 | 24.0 | 5232 | 0.2267 | 0.9059 | 0.9897 | 0.9829 | -1.0 | 0.2171 | 0.9077 | 0.4861 | 0.9328 | 0.9341 | -1.0 | 0.2818 | 0.9371 | 0.9253 | 0.9488 | 0.8864 | 0.9193 |
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+ | 0.2812 | 25.0 | 5450 | 0.2326 | 0.9057 | 0.9899 | 0.9758 | -1.0 | 0.1995 | 0.9097 | 0.4837 | 0.9316 | 0.9326 | -1.0 | 0.2286 | 0.9371 | 0.9196 | 0.9449 | 0.8917 | 0.9202 |
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+ | 0.26 | 26.0 | 5668 | 0.2111 | 0.915 | 0.9899 | 0.9792 | 0.0 | 0.2832 | 0.9199 | 0.4902 | 0.9408 | 0.9423 | 0.0 | 0.415 | 0.9457 | 0.9267 | 0.9521 | 0.9032 | 0.9325 |
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+ | 0.26 | 27.0 | 5886 | 0.2184 | 0.9132 | 0.9898 | 0.9764 | -1.0 | 0.2546 | 0.9167 | 0.4872 | 0.9375 | 0.9389 | -1.0 | 0.2767 | 0.943 | 0.9277 | 0.95 | 0.8988 | 0.9279 |
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+ | 0.2498 | 28.0 | 6104 | 0.2200 | 0.9159 | 0.9892 | 0.9756 | -1.0 | 0.1921 | 0.9197 | 0.4872 | 0.9397 | 0.9413 | -1.0 | 0.275 | 0.9446 | 0.9314 | 0.9547 | 0.9004 | 0.9279 |
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+ | 0.2498 | 29.0 | 6322 | 0.2075 | 0.9209 | 0.9899 | 0.9791 | -1.0 | 0.317 | 0.9241 | 0.4904 | 0.9448 | 0.9454 | -1.0 | 0.34 | 0.9475 | 0.9345 | 0.9565 | 0.9073 | 0.9342 |
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+ | 0.2519 | 30.0 | 6540 | 0.2068 | 0.9189 | 0.9898 | 0.9755 | -1.0 | 0.1871 | 0.9234 | 0.49 | 0.9447 | 0.9466 | -1.0 | 0.2615 | 0.9505 | 0.935 | 0.9592 | 0.9027 | 0.9341 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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- oid sha256:209deaece8ab81cf075ad38dec7b86e25ae15aa438fcd23976520a114118c8b0
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  size 174076712
 
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