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End of training

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  1. README.md +70 -40
  2. model.safetensors +1 -1
  3. runs/Jan21_03-49-08_jupyter-admin01/events.out.tfevents.1737431456.jupyter-admin01.195.0 +3 -0
  4. runs/Jan21_03-54-06_jupyter-admin01/events.out.tfevents.1737431661.jupyter-admin01.195.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -18,21 +18,21 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the segments/sidewalk-semantic dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.7572
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- - Mean Iou: 0.1572
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- - Mean Accuracy: 0.2026
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- - Overall Accuracy: 0.7348
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  - Accuracy Unlabeled: nan
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- - Accuracy Flat-road: 0.8331
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- - Accuracy Flat-sidewalk: 0.9417
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  - Accuracy Flat-crosswalk: 0.0
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- - Accuracy Flat-cyclinglane: 0.4061
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- - Accuracy Flat-parkingdriveway: 0.0000
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  - Accuracy Flat-railtrack: nan
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- - Accuracy Flat-curb: 0.0
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  - Accuracy Human-person: 0.0
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  - Accuracy Human-rider: 0.0
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- - Accuracy Vehicle-car: 0.8264
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  - Accuracy Vehicle-truck: 0.0
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  - Accuracy Vehicle-bus: 0.0
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  - Accuracy Vehicle-tramtrain: 0.0
@@ -40,9 +40,9 @@ It achieves the following results on the evaluation set:
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  - Accuracy Vehicle-bicycle: 0.0
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  - Accuracy Vehicle-caravan: 0.0
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  - Accuracy Vehicle-cartrailer: 0.0
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- - Accuracy Construction-building: 0.9336
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  - Accuracy Construction-door: 0.0
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- - Accuracy Construction-wall: 0.0
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  - Accuracy Construction-fenceguardrail: 0.0
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  - Accuracy Construction-bridge: 0.0
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  - Accuracy Construction-tunnel: nan
@@ -50,24 +50,24 @@ It achieves the following results on the evaluation set:
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  - Accuracy Object-pole: 0.0
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  - Accuracy Object-trafficsign: 0.0
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  - Accuracy Object-trafficlight: 0.0
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- - Accuracy Nature-vegetation: 0.9269
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- - Accuracy Nature-terrain: 0.7894
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- - Accuracy Sky: 0.8244
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  - Accuracy Void-ground: 0.0
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  - Accuracy Void-dynamic: 0.0
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- - Accuracy Void-static: 0.0001
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  - Accuracy Void-unclear: 0.0
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  - Iou Unlabeled: nan
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- - Iou Flat-road: 0.5074
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- - Iou Flat-sidewalk: 0.7790
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  - Iou Flat-crosswalk: 0.0
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- - Iou Flat-cyclinglane: 0.3846
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- - Iou Flat-parkingdriveway: 0.0000
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  - Iou Flat-railtrack: nan
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- - Iou Flat-curb: 0.0
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  - Iou Human-person: 0.0
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  - Iou Human-rider: 0.0
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- - Iou Vehicle-car: 0.6400
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  - Iou Vehicle-truck: 0.0
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  - Iou Vehicle-bus: 0.0
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  - Iou Vehicle-tramtrain: 0.0
@@ -75,9 +75,9 @@ It achieves the following results on the evaluation set:
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  - Iou Vehicle-bicycle: 0.0
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  - Iou Vehicle-caravan: 0.0
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  - Iou Vehicle-cartrailer: 0.0
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- - Iou Construction-building: 0.5340
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  - Iou Construction-door: 0.0
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- - Iou Construction-wall: 0.0
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  - Iou Construction-fenceguardrail: 0.0
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  - Iou Construction-bridge: 0.0
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  - Iou Construction-tunnel: nan
@@ -85,12 +85,12 @@ It achieves the following results on the evaluation set:
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  - Iou Object-pole: 0.0
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  - Iou Object-trafficsign: 0.0
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  - Iou Object-trafficlight: 0.0
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- - Iou Nature-vegetation: 0.7395
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- - Iou Nature-terrain: 0.6519
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- - Iou Sky: 0.7934
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  - Iou Void-ground: 0.0
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  - Iou Void-dynamic: 0.0
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- - Iou Void-static: 0.0001
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  - Iou Void-unclear: 0.0
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  ## Model description
@@ -111,8 +111,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 6e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
116
  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
@@ -122,16 +122,46 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Flat-road | Accuracy Flat-sidewalk | Accuracy Flat-crosswalk | Accuracy Flat-cyclinglane | Accuracy Flat-parkingdriveway | Accuracy Flat-railtrack | Accuracy Flat-curb | Accuracy Human-person | Accuracy Human-rider | Accuracy Vehicle-car | Accuracy Vehicle-truck | Accuracy Vehicle-bus | Accuracy Vehicle-tramtrain | Accuracy Vehicle-motorcycle | Accuracy Vehicle-bicycle | Accuracy Vehicle-caravan | Accuracy Vehicle-cartrailer | Accuracy Construction-building | Accuracy Construction-door | Accuracy Construction-wall | Accuracy Construction-fenceguardrail | Accuracy Construction-bridge | Accuracy Construction-tunnel | Accuracy Construction-stairs | Accuracy Object-pole | Accuracy Object-trafficsign | Accuracy Object-trafficlight | Accuracy Nature-vegetation | Accuracy Nature-terrain | Accuracy Sky | Accuracy Void-ground | Accuracy Void-dynamic | Accuracy Void-static | Accuracy Void-unclear | Iou Unlabeled | Iou Flat-road | Iou Flat-sidewalk | Iou Flat-crosswalk | Iou Flat-cyclinglane | Iou Flat-parkingdriveway | Iou Flat-railtrack | Iou Flat-curb | Iou Human-person | Iou Human-rider | Iou Vehicle-car | Iou Vehicle-truck | Iou Vehicle-bus | Iou Vehicle-tramtrain | Iou Vehicle-motorcycle | Iou Vehicle-bicycle | Iou Vehicle-caravan | Iou Vehicle-cartrailer | Iou Construction-building | Iou Construction-door | Iou Construction-wall | Iou Construction-fenceguardrail | Iou Construction-bridge | Iou Construction-tunnel | Iou Construction-stairs | Iou Object-pole | Iou Object-trafficsign | Iou Object-trafficlight | Iou Nature-vegetation | Iou Nature-terrain | Iou Sky | Iou Void-ground | Iou Void-dynamic | Iou Void-static | Iou Void-unclear |
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- | 2.9583 | 0.2 | 20 | 2.8947 | 0.0659 | 0.1061 | 0.5330 | nan | 0.3554 | 0.9554 | 0.0039 | 0.0246 | 0.0078 | nan | 0.0165 | 0.0 | 0.0 | 0.0859 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0063 | 0.0 | 0.0049 | 0.9672 | 0.0 | 0.0 | 0.0030 | 0.0 | nan | 0.0 | 0.0041 | 0.0 | 0.0 | 0.4506 | 0.2841 | 0.1762 | 0.0060 | 0.0 | 0.0425 | 0.0 | 0.0 | 0.3070 | 0.6475 | 0.0037 | 0.0241 | 0.0064 | 0.0 | 0.0150 | 0.0 | 0.0 | 0.0854 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0016 | 0.0 | 0.0000 | 0.3220 | 0.0 | 0.0 | 0.0025 | 0.0 | 0.0 | 0.0 | 0.0019 | 0.0 | 0.0 | 0.4297 | 0.2759 | 0.1531 | 0.0057 | 0.0 | 0.0234 | 0.0 |
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- | 2.6766 | 0.4 | 40 | 2.4916 | 0.1178 | 0.1647 | 0.6644 | nan | 0.6530 | 0.9419 | 0.0023 | 0.3313 | 0.0014 | nan | 0.0010 | 0.0 | 0.0 | 0.5738 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.0 | 0.0 | 0.9821 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0006 | 0.0 | 0.0 | 0.8088 | 0.5875 | 0.3451 | 0.0 | 0.0 | 0.0365 | 0.0 | 0.0 | 0.4804 | 0.7202 | 0.0022 | 0.3100 | 0.0013 | 0.0 | 0.0010 | 0.0 | 0.0 | 0.5270 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0030 | 0.0 | 0.0 | 0.3895 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0006 | 0.0 | 0.0 | 0.6833 | 0.5181 | 0.3377 | 0.0 | 0.0 | 0.0292 | 0.0 |
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- | 2.408 | 0.6 | 60 | 2.2810 | 0.1381 | 0.1826 | 0.6944 | nan | 0.7519 | 0.9343 | 0.0028 | 0.2944 | 0.0004 | nan | 0.0007 | 0.0 | 0.0 | 0.6684 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0001 | 0.0 | 0.0 | 0.8449 | 0.7784 | 0.5831 | 0.0 | 0.0 | 0.0102 | 0.0 | nan | 0.4821 | 0.7372 | 0.0028 | 0.2809 | 0.0004 | nan | 0.0007 | 0.0 | 0.0 | 0.5936 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4440 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0001 | 0.0 | 0.0 | 0.7242 | 0.5659 | 0.5772 | 0.0 | 0.0 | 0.0096 | 0.0 |
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- | 2.2384 | 0.8 | 80 | 2.1288 | 0.1448 | 0.1896 | 0.7085 | nan | 0.7963 | 0.9307 | 0.0 | 0.2569 | 0.0002 | nan | 0.0001 | 0.0 | 0.0 | 0.7599 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9598 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8970 | 0.7350 | 0.7258 | 0.0 | 0.0 | 0.0062 | 0.0 | nan | 0.4728 | 0.7520 | 0.0 | 0.2470 | 0.0002 | nan | 0.0001 | 0.0 | 0.0 | 0.6156 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4871 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7358 | 0.6074 | 0.7109 | 0.0 | 0.0 | 0.0060 | 0.0 |
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- | 2.1473 | 1.0 | 100 | 1.9242 | 0.1509 | 0.1949 | 0.7204 | nan | 0.7782 | 0.9431 | 0.0 | 0.3620 | 0.0002 | nan | 0.0001 | 0.0 | 0.0 | 0.7362 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9514 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9083 | 0.7771 | 0.7789 | 0.0 | 0.0 | 0.0013 | 0.0 | nan | 0.5079 | 0.7515 | 0.0 | 0.3449 | 0.0002 | nan | 0.0001 | 0.0 | 0.0 | 0.6134 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4960 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7341 | 0.6213 | 0.7572 | 0.0 | 0.0 | 0.0013 | 0.0 |
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- | 1.9295 | 1.2 | 120 | 1.8798 | 0.1532 | 0.1980 | 0.7269 | nan | 0.7610 | 0.9558 | 0.0 | 0.3789 | 0.0004 | nan | 0.0000 | 0.0 | 0.0 | 0.8360 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9369 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9149 | 0.7665 | 0.7863 | 0.0 | 0.0 | 0.0006 | 0.0 | nan | 0.5222 | 0.7457 | 0.0 | 0.3602 | 0.0004 | nan | 0.0000 | 0.0 | 0.0 | 0.6204 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5233 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7413 | 0.6259 | 0.7617 | 0.0 | 0.0 | 0.0006 | 0.0 |
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- | 1.7913 | 1.4 | 140 | 1.8440 | 0.1558 | 0.2002 | 0.7309 | nan | 0.8095 | 0.9399 | 0.0 | 0.4413 | 0.0001 | nan | 0.0000 | 0.0 | 0.0 | 0.7851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9422 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9265 | 0.7520 | 0.8104 | 0.0 | 0.0 | 0.0002 | 0.0 | nan | 0.5152 | 0.7690 | 0.0 | 0.4097 | 0.0001 | nan | 0.0000 | 0.0 | 0.0 | 0.6310 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5166 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7325 | 0.6291 | 0.7832 | 0.0 | 0.0 | 0.0002 | 0.0 |
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- | 1.7844 | 1.6 | 160 | 1.7836 | 0.1569 | 0.2020 | 0.7340 | nan | 0.8135 | 0.9470 | 0.0 | 0.4117 | 0.0003 | nan | 0.0000 | 0.0 | 0.0 | 0.8246 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9397 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9193 | 0.7826 | 0.8254 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.5193 | 0.7701 | 0.0 | 0.3898 | 0.0003 | nan | 0.0000 | 0.0 | 0.0 | 0.6350 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5248 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7433 | 0.6461 | 0.7926 | 0.0 | 0.0 | 0.0000 | 0.0 |
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- | 1.7999 | 1.8 | 180 | 1.7544 | 0.1575 | 0.2022 | 0.7353 | nan | 0.8022 | 0.9522 | 0.0 | 0.4115 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.8304 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9327 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9254 | 0.7855 | 0.8305 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.5240 | 0.7646 | 0.0 | 0.3900 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.6385 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5348 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7411 | 0.6504 | 0.7967 | 0.0 | 0.0 | 0.0000 | 0.0 |
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- | 1.7429 | 2.0 | 200 | 1.7572 | 0.1572 | 0.2026 | 0.7348 | nan | 0.8331 | 0.9417 | 0.0 | 0.4061 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.8264 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9336 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9269 | 0.7894 | 0.8244 | 0.0 | 0.0 | 0.0001 | 0.0 | nan | 0.5074 | 0.7790 | 0.0 | 0.3846 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.6400 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5340 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7395 | 0.6519 | 0.7934 | 0.0 | 0.0 | 0.0001 | 0.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the segments/sidewalk-semantic dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8640
22
+ - Mean Iou: 0.1813
23
+ - Mean Accuracy: 0.2233
24
+ - Overall Accuracy: 0.7956
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  - Accuracy Unlabeled: nan
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+ - Accuracy Flat-road: 0.9372
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+ - Accuracy Flat-sidewalk: 0.9555
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  - Accuracy Flat-crosswalk: 0.0
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+ - Accuracy Flat-cyclinglane: 0.6635
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+ - Accuracy Flat-parkingdriveway: 0.0799
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  - Accuracy Flat-railtrack: nan
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+ - Accuracy Flat-curb: 0.0001
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  - Accuracy Human-person: 0.0
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  - Accuracy Human-rider: 0.0
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+ - Accuracy Vehicle-car: 0.8975
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  - Accuracy Vehicle-truck: 0.0
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  - Accuracy Vehicle-bus: 0.0
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  - Accuracy Vehicle-tramtrain: 0.0
 
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  - Accuracy Vehicle-bicycle: 0.0
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  - Accuracy Vehicle-caravan: 0.0
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  - Accuracy Vehicle-cartrailer: 0.0
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+ - Accuracy Construction-building: 0.9214
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  - Accuracy Construction-door: 0.0
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+ - Accuracy Construction-wall: 0.0000
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  - Accuracy Construction-fenceguardrail: 0.0
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  - Accuracy Construction-bridge: 0.0
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  - Accuracy Construction-tunnel: nan
 
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  - Accuracy Object-pole: 0.0
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  - Accuracy Object-trafficsign: 0.0
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  - Accuracy Object-trafficlight: 0.0
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+ - Accuracy Nature-vegetation: 0.9128
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+ - Accuracy Nature-terrain: 0.8493
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+ - Accuracy Sky: 0.9299
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  - Accuracy Void-ground: 0.0
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  - Accuracy Void-dynamic: 0.0
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+ - Accuracy Void-static: 0.0
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  - Accuracy Void-unclear: 0.0
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  - Iou Unlabeled: nan
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+ - Iou Flat-road: 0.6819
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+ - Iou Flat-sidewalk: 0.8378
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  - Iou Flat-crosswalk: 0.0
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+ - Iou Flat-cyclinglane: 0.5970
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+ - Iou Flat-parkingdriveway: 0.0754
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  - Iou Flat-railtrack: nan
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+ - Iou Flat-curb: 0.0001
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  - Iou Human-person: 0.0
69
  - Iou Human-rider: 0.0
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+ - Iou Vehicle-car: 0.7287
71
  - Iou Vehicle-truck: 0.0
72
  - Iou Vehicle-bus: 0.0
73
  - Iou Vehicle-tramtrain: 0.0
 
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  - Iou Vehicle-bicycle: 0.0
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  - Iou Vehicle-caravan: 0.0
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  - Iou Vehicle-cartrailer: 0.0
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+ - Iou Construction-building: 0.5594
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  - Iou Construction-door: 0.0
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+ - Iou Construction-wall: 0.0000
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  - Iou Construction-fenceguardrail: 0.0
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  - Iou Construction-bridge: 0.0
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  - Iou Construction-tunnel: nan
 
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  - Iou Object-pole: 0.0
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  - Iou Object-trafficsign: 0.0
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  - Iou Object-trafficlight: 0.0
88
+ - Iou Nature-vegetation: 0.7763
89
+ - Iou Nature-terrain: 0.6951
90
+ - Iou Sky: 0.8496
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  - Iou Void-ground: 0.0
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  - Iou Void-dynamic: 0.0
93
+ - Iou Void-static: 0.0
94
  - Iou Void-unclear: 0.0
95
 
96
  ## Model description
 
111
 
112
  The following hyperparameters were used during training:
113
  - learning_rate: 6e-05
114
+ - train_batch_size: 2
115
+ - eval_batch_size: 2
116
  - seed: 42
117
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
118
  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Flat-road | Accuracy Flat-sidewalk | Accuracy Flat-crosswalk | Accuracy Flat-cyclinglane | Accuracy Flat-parkingdriveway | Accuracy Flat-railtrack | Accuracy Flat-curb | Accuracy Human-person | Accuracy Human-rider | Accuracy Vehicle-car | Accuracy Vehicle-truck | Accuracy Vehicle-bus | Accuracy Vehicle-tramtrain | Accuracy Vehicle-motorcycle | Accuracy Vehicle-bicycle | Accuracy Vehicle-caravan | Accuracy Vehicle-cartrailer | Accuracy Construction-building | Accuracy Construction-door | Accuracy Construction-wall | Accuracy Construction-fenceguardrail | Accuracy Construction-bridge | Accuracy Construction-tunnel | Accuracy Construction-stairs | Accuracy Object-pole | Accuracy Object-trafficsign | Accuracy Object-trafficlight | Accuracy Nature-vegetation | Accuracy Nature-terrain | Accuracy Sky | Accuracy Void-ground | Accuracy Void-dynamic | Accuracy Void-static | Accuracy Void-unclear | Iou Unlabeled | Iou Flat-road | Iou Flat-sidewalk | Iou Flat-crosswalk | Iou Flat-cyclinglane | Iou Flat-parkingdriveway | Iou Flat-railtrack | Iou Flat-curb | Iou Human-person | Iou Human-rider | Iou Vehicle-car | Iou Vehicle-truck | Iou Vehicle-bus | Iou Vehicle-tramtrain | Iou Vehicle-motorcycle | Iou Vehicle-bicycle | Iou Vehicle-caravan | Iou Vehicle-cartrailer | Iou Construction-building | Iou Construction-door | Iou Construction-wall | Iou Construction-fenceguardrail | Iou Construction-bridge | Iou Construction-tunnel | Iou Construction-stairs | Iou Object-pole | Iou Object-trafficsign | Iou Object-trafficlight | Iou Nature-vegetation | Iou Nature-terrain | Iou Sky | Iou Void-ground | Iou Void-dynamic | Iou Void-static | Iou Void-unclear |
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125
+ | 2.9097 | 0.05 | 20 | 2.4129 | 0.0976 | 0.1470 | 0.6553 | nan | 0.6590 | 0.9442 | 0.0 | 0.0820 | 0.0057 | nan | 0.0033 | 0.0000 | 0.0 | 0.6208 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0176 | 0.0 | 0.0 | 0.5921 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9758 | 0.0306 | 0.7320 | 0.0002 | 0.0 | 0.0402 | 0.0 | 0.0 | 0.4482 | 0.7368 | 0.0 | 0.0774 | 0.0057 | 0.0 | 0.0030 | 0.0000 | 0.0 | 0.4563 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0140 | 0.0 | 0.0 | 0.4050 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5114 | 0.0299 | 0.6961 | 0.0002 | 0.0 | 0.0302 | 0.0 |
126
+ | 2.2468 | 0.1 | 40 | 2.2262 | 0.1037 | 0.1504 | 0.6653 | nan | 0.8040 | 0.8979 | 0.0 | 0.0072 | 0.0016 | nan | 0.0004 | 0.0 | 0.0 | 0.4835 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0006 | 0.0 | 0.0 | 0.8209 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9612 | 0.0184 | 0.8068 | 0.0 | 0.0 | 0.0106 | 0.0 | nan | 0.4453 | 0.7623 | 0.0 | 0.0070 | 0.0016 | 0.0 | 0.0004 | 0.0 | 0.0 | 0.4186 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0006 | 0.0 | 0.0 | 0.4512 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5601 | 0.0182 | 0.7458 | 0.0 | 0.0 | 0.0104 | 0.0 |
127
+ | 1.925 | 0.15 | 60 | 2.0682 | 0.1164 | 0.1590 | 0.6842 | nan | 0.8002 | 0.9212 | 0.0 | 0.0815 | 0.0005 | nan | 0.0 | 0.0 | 0.0 | 0.4581 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8328 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9535 | 0.1864 | 0.8544 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.4820 | 0.7689 | 0.0 | 0.0802 | 0.0005 | nan | 0.0 | 0.0 | 0.0 | 0.4091 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4382 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5993 | 0.1795 | 0.7682 | 0.0 | 0.0 | 0.0000 | 0.0 |
128
+ | 2.3829 | 0.2 | 80 | 1.8790 | 0.1358 | 0.1780 | 0.7131 | nan | 0.8259 | 0.9218 | 0.0 | 0.2819 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.5001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8609 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9421 | 0.4796 | 0.8829 | 0.0 | 0.0 | 0.0000 | 0.0 | nan | 0.5192 | 0.7818 | 0.0 | 0.2719 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.4260 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4509 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6537 | 0.4571 | 0.7836 | 0.0 | 0.0 | 0.0000 | 0.0 |
129
+ | 1.6895 | 0.25 | 100 | 1.7516 | 0.1275 | 0.1719 | 0.7009 | nan | 0.8793 | 0.8949 | 0.0 | 0.2101 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.5551 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8658 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9496 | 0.2505 | 0.8940 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4903 | 0.7883 | 0.0 | 0.2059 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.4758 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4736 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6125 | 0.2442 | 0.7891 | 0.0 | 0.0 | 0.0 | 0.0 |
130
+ | 2.0938 | 0.3 | 120 | 1.6307 | 0.1428 | 0.1812 | 0.7269 | nan | 0.7659 | 0.9636 | 0.0 | 0.2570 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.6130 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8365 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9509 | 0.5413 | 0.8706 | 0.0 | 0.0 | 0.0001 | 0.0 | nan | 0.5601 | 0.7606 | 0.0 | 0.2490 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.5441 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4929 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6511 | 0.5149 | 0.7966 | 0.0 | 0.0 | 0.0001 | 0.0 |
131
+ | 1.6363 | 0.35 | 140 | 1.4988 | 0.1522 | 0.1931 | 0.7447 | nan | 0.8234 | 0.9534 | 0.0 | 0.4649 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.6198 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8628 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9422 | 0.6012 | 0.9106 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6114 | 0.7902 | 0.0 | 0.4050 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.5380 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4899 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6747 | 0.5672 | 0.7937 | 0.0 | 0.0 | 0.0 | 0.0 |
132
+ | 1.7375 | 0.4 | 160 | 1.4685 | 0.1521 | 0.1922 | 0.7444 | nan | 0.8202 | 0.9583 | 0.0 | 0.4191 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.5643 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9003 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9231 | 0.6577 | 0.9072 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6212 | 0.7871 | 0.0 | 0.3807 | 0.0000 | nan | 0.0 | 0.0 | 0.0 | 0.4978 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4735 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7028 | 0.6064 | 0.7976 | 0.0 | 0.0 | 0.0 | 0.0 |
133
+ | 1.5994 | 0.45 | 180 | 1.3911 | 0.1559 | 0.1979 | 0.7545 | nan | 0.8985 | 0.9464 | 0.0 | 0.3306 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.7378 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8685 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9345 | 0.7326 | 0.8831 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5703 | 0.8161 | 0.0 | 0.3218 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.5994 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5232 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7016 | 0.6663 | 0.7904 | 0.0 | 0.0 | 0.0 | 0.0 |
134
+ | 2.0048 | 0.5 | 200 | 1.3081 | 0.1578 | 0.1978 | 0.7541 | nan | 0.7970 | 0.9670 | 0.0 | 0.4200 | 0.0003 | nan | 0.0 | 0.0 | 0.0 | 0.7116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8340 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9554 | 0.7548 | 0.8900 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6425 | 0.7818 | 0.0 | 0.3644 | 0.0003 | nan | 0.0 | 0.0 | 0.0 | 0.6015 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5267 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6703 | 0.6692 | 0.7928 | 0.0 | 0.0 | 0.0 | 0.0 |
135
+ | 1.4191 | 0.55 | 220 | 1.2710 | 0.1621 | 0.2014 | 0.7633 | nan | 0.8450 | 0.9635 | 0.0 | 0.3623 | 0.0013 | nan | 0.0 | 0.0 | 0.0 | 0.7991 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9186 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9269 | 0.7738 | 0.8549 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6466 | 0.7850 | 0.0 | 0.3533 | 0.0013 | nan | 0.0 | 0.0 | 0.0 | 0.6419 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5394 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7239 | 0.6741 | 0.8204 | 0.0 | 0.0 | 0.0 | 0.0 |
136
+ | 1.2046 | 0.6 | 240 | 1.2596 | 0.1623 | 0.2054 | 0.7580 | nan | 0.9143 | 0.9102 | 0.0 | 0.6029 | 0.0011 | nan | 0.0 | 0.0 | 0.0 | 0.7193 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9179 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9449 | 0.6649 | 0.8957 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5819 | 0.8199 | 0.0 | 0.5105 | 0.0011 | nan | 0.0 | 0.0 | 0.0 | 0.6122 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5208 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.6951 | 0.6131 | 0.8401 | 0.0 | 0.0 | 0.0 | 0.0 |
137
+ | 2.3716 | 0.65 | 260 | 1.2121 | 0.1652 | 0.2072 | 0.7702 | nan | 0.9240 | 0.9416 | 0.0 | 0.5131 | 0.0005 | nan | 0.0 | 0.0 | 0.0 | 0.8518 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8971 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9395 | 0.6577 | 0.9059 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6001 | 0.8232 | 0.0 | 0.4777 | 0.0005 | nan | 0.0 | 0.0 | 0.0 | 0.6470 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5700 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7144 | 0.6094 | 0.8436 | 0.0 | 0.0 | 0.0 | 0.0 |
138
+ | 1.1683 | 0.7 | 280 | 1.1438 | 0.1706 | 0.2117 | 0.7786 | nan | 0.8707 | 0.9609 | 0.0 | 0.6311 | 0.0007 | nan | 0.0 | 0.0 | 0.0 | 0.8191 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9206 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9257 | 0.7316 | 0.9131 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6810 | 0.8121 | 0.0 | 0.5472 | 0.0007 | nan | 0.0 | 0.0 | 0.0 | 0.6511 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5441 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7346 | 0.6461 | 0.8426 | 0.0 | 0.0 | 0.0 | 0.0 |
139
+ | 1.2216 | 0.75 | 300 | 1.1543 | 0.1685 | 0.2111 | 0.7765 | nan | 0.9293 | 0.9435 | 0.0 | 0.5694 | 0.0006 | nan | 0.0 | 0.0 | 0.0 | 0.8627 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8790 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9470 | 0.7174 | 0.9055 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6241 | 0.8300 | 0.0 | 0.5381 | 0.0006 | nan | 0.0 | 0.0 | 0.0 | 0.6406 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5680 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7144 | 0.6421 | 0.8326 | 0.0 | 0.0 | 0.0 | 0.0 |
140
+ | 1.0353 | 0.8 | 320 | 1.1280 | 0.1609 | 0.2030 | 0.7583 | nan | 0.9576 | 0.9160 | 0.0 | 0.4185 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.7980 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9393 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9169 | 0.6555 | 0.8954 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.5528 | 0.8267 | 0.0 | 0.4079 | 0.0001 | nan | 0.0 | 0.0 | 0.0 | 0.6672 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5294 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7287 | 0.5931 | 0.8417 | 0.0 | 0.0 | 0.0 | 0.0 |
141
+ | 1.2914 | 0.85 | 340 | 1.0709 | 0.1669 | 0.2087 | 0.7767 | nan | 0.8841 | 0.9690 | 0.0 | 0.4128 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.8989 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8778 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9331 | 0.7791 | 0.9226 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6624 | 0.8036 | 0.0 | 0.4016 | 0.0002 | nan | 0.0 | 0.0 | 0.0 | 0.6614 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5705 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7446 | 0.6539 | 0.8414 | 0.0 | 0.0 | 0.0 | 0.0 |
142
+ | 1.04 | 0.9 | 360 | 1.0501 | 0.1711 | 0.2155 | 0.7789 | nan | 0.9411 | 0.9289 | 0.0 | 0.5881 | 0.0009 | nan | 0.0 | 0.0 | 0.0 | 0.8622 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9081 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9310 | 0.8356 | 0.9012 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6170 | 0.8329 | 0.0 | 0.5329 | 0.0009 | nan | 0.0 | 0.0 | 0.0 | 0.6817 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5572 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7424 | 0.6656 | 0.8460 | 0.0 | 0.0 | 0.0 | 0.0 |
143
+ | 1.3936 | 0.95 | 380 | 1.0156 | 0.1704 | 0.2137 | 0.7769 | nan | 0.9314 | 0.9340 | 0.0 | 0.5883 | 0.0041 | nan | 0.0 | 0.0 | 0.0 | 0.8612 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8653 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9497 | 0.7963 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6222 | 0.8216 | 0.0 | 0.5566 | 0.0041 | nan | 0.0 | 0.0 | 0.0 | 0.6814 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5725 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7117 | 0.6494 | 0.8339 | 0.0 | 0.0 | 0.0 | 0.0 |
144
+ | 1.0755 | 1.0 | 400 | 1.0207 | 0.1699 | 0.2136 | 0.7785 | nan | 0.9235 | 0.9450 | 0.0 | 0.5502 | 0.0009 | nan | 0.0 | 0.0 | 0.0 | 0.9010 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8852 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9251 | 0.7857 | 0.9188 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6156 | 0.8246 | 0.0 | 0.5239 | 0.0009 | nan | 0.0 | 0.0 | 0.0 | 0.6712 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5672 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7448 | 0.6645 | 0.8251 | 0.0 | 0.0 | 0.0 | 0.0 |
145
+ | 0.9754 | 1.05 | 420 | 0.9999 | 0.1744 | 0.2183 | 0.7868 | nan | 0.9275 | 0.9491 | 0.0 | 0.6556 | 0.0032 | nan | 0.0 | 0.0 | 0.0 | 0.8851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8986 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9194 | 0.8269 | 0.9203 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6496 | 0.8305 | 0.0 | 0.5666 | 0.0032 | nan | 0.0 | 0.0 | 0.0 | 0.6863 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5681 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7582 | 0.6836 | 0.8350 | 0.0 | 0.0 | 0.0 | 0.0 |
146
+ | 1.2134 | 1.1 | 440 | 0.9553 | 0.1736 | 0.2182 | 0.7841 | nan | 0.9338 | 0.9361 | 0.0 | 0.6495 | 0.0132 | nan | 0.0 | 0.0 | 0.0 | 0.8674 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9159 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9247 | 0.8396 | 0.9013 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6456 | 0.8346 | 0.0 | 0.5679 | 0.0131 | nan | 0.0 | 0.0 | 0.0 | 0.6805 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5559 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7527 | 0.6596 | 0.8452 | 0.0 | 0.0 | 0.0 | 0.0 |
147
+ | 1.0486 | 1.15 | 460 | 0.9654 | 0.1713 | 0.2152 | 0.7795 | nan | 0.9483 | 0.9307 | 0.0 | 0.5519 | 0.0128 | nan | 0.0 | 0.0 | 0.0 | 0.8840 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8885 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9438 | 0.8156 | 0.9099 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6150 | 0.8302 | 0.0 | 0.5254 | 0.0127 | nan | 0.0 | 0.0 | 0.0 | 0.6839 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5836 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7245 | 0.6576 | 0.8476 | 0.0 | 0.0 | 0.0 | 0.0 |
148
+ | 1.4786 | 1.2 | 480 | 0.9317 | 0.1756 | 0.2183 | 0.7891 | nan | 0.9250 | 0.9547 | 0.0 | 0.6636 | 0.0136 | nan | 0.0 | 0.0 | 0.0 | 0.8882 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9153 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9228 | 0.7705 | 0.9308 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6901 | 0.8278 | 0.0 | 0.5496 | 0.0135 | nan | 0.0 | 0.0 | 0.0 | 0.7016 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5615 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7577 | 0.6675 | 0.8495 | 0.0 | 0.0 | 0.0 | 0.0 |
149
+ | 0.861 | 1.25 | 500 | 0.9472 | 0.1729 | 0.2145 | 0.7849 | nan | 0.9310 | 0.9541 | 0.0 | 0.5750 | 0.0191 | nan | 0.0 | 0.0 | 0.0 | 0.8967 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9062 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9373 | 0.7201 | 0.9248 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6869 | 0.8236 | 0.0 | 0.5153 | 0.0188 | nan | 0.0 | 0.0 | 0.0 | 0.6985 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5649 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7351 | 0.6375 | 0.8513 | 0.0 | 0.0 | 0.0 | 0.0 |
150
+ | 0.8521 | 1.3 | 520 | 0.9387 | 0.1754 | 0.2175 | 0.7852 | nan | 0.9459 | 0.9409 | 0.0 | 0.5862 | 0.0391 | nan | 0.0 | 0.0 | 0.0 | 0.8778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9179 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9274 | 0.8059 | 0.9185 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6392 | 0.8315 | 0.0 | 0.5525 | 0.0383 | nan | 0.0 | 0.0 | 0.0 | 0.7149 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5561 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7556 | 0.6739 | 0.8523 | 0.0 | 0.0 | 0.0 | 0.0 |
151
+ | 1.8729 | 1.35 | 540 | 0.9124 | 0.1767 | 0.2181 | 0.7869 | nan | 0.9405 | 0.9449 | 0.0 | 0.6155 | 0.0486 | nan | 0.0000 | 0.0 | 0.0 | 0.8884 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9140 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9311 | 0.7752 | 0.9202 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6594 | 0.8249 | 0.0 | 0.5603 | 0.0471 | nan | 0.0000 | 0.0 | 0.0 | 0.7207 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5630 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7527 | 0.6722 | 0.8533 | 0.0 | 0.0 | 0.0 | 0.0 |
152
+ | 0.9849 | 1.4 | 560 | 0.9113 | 0.1781 | 0.2223 | 0.7883 | nan | 0.9474 | 0.9323 | 0.0 | 0.7026 | 0.0366 | nan | 0.0000 | 0.0 | 0.0 | 0.9012 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9031 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9198 | 0.8473 | 0.9240 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6448 | 0.8255 | 0.0 | 0.5907 | 0.0357 | nan | 0.0000 | 0.0 | 0.0 | 0.7192 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5728 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7640 | 0.6903 | 0.8553 | 0.0 | 0.0 | 0.0 | 0.0 |
153
+ | 0.7368 | 1.45 | 580 | 0.9020 | 0.1797 | 0.2219 | 0.7919 | nan | 0.9410 | 0.9434 | 0.0 | 0.7123 | 0.0395 | nan | 0.0000 | 0.0 | 0.0 | 0.8789 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9184 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9260 | 0.8265 | 0.9163 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6703 | 0.8327 | 0.0 | 0.6143 | 0.0386 | nan | 0.0000 | 0.0 | 0.0 | 0.7178 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5594 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7605 | 0.7026 | 0.8538 | 0.0 | 0.0 | 0.0 | 0.0 |
154
+ | 0.8884 | 1.5 | 600 | 0.9055 | 0.1789 | 0.2201 | 0.7927 | nan | 0.9278 | 0.9592 | 0.0 | 0.6248 | 0.0399 | nan | 0.0 | 0.0 | 0.0 | 0.9106 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9110 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9228 | 0.8225 | 0.9229 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6812 | 0.8265 | 0.0 | 0.5748 | 0.0387 | nan | 0.0 | 0.0 | 0.0 | 0.7103 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5692 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7681 | 0.7012 | 0.8540 | 0.0 | 0.0 | 0.0 | 0.0 |
155
+ | 0.7291 | 1.55 | 620 | 0.9008 | 0.1787 | 0.2228 | 0.7900 | nan | 0.9461 | 0.9404 | 0.0 | 0.6101 | 0.1005 | nan | 0.0000 | 0.0 | 0.0 | 0.9062 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9094 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9155 | 0.8713 | 0.9290 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6276 | 0.8469 | 0.0 | 0.5788 | 0.0962 | nan | 0.0000 | 0.0 | 0.0 | 0.7110 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5622 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7648 | 0.6880 | 0.8430 | 0.0 | 0.0 | 0.0 | 0.0 |
156
+ | 0.7366 | 1.6 | 640 | 0.8804 | 0.1799 | 0.2250 | 0.7942 | nan | 0.9457 | 0.9424 | 0.0 | 0.7139 | 0.0687 | nan | 0.0 | 0.0 | 0.0 | 0.9156 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9051 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9154 | 0.8601 | 0.9338 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6548 | 0.8488 | 0.0 | 0.6189 | 0.0666 | nan | 0.0 | 0.0 | 0.0 | 0.7035 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5631 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7690 | 0.6915 | 0.8419 | 0.0 | 0.0 | 0.0 | 0.0 |
157
+ | 0.8606 | 1.65 | 660 | 0.8687 | 0.1812 | 0.2249 | 0.7965 | nan | 0.9329 | 0.9527 | 0.0 | 0.7145 | 0.0836 | nan | 0.0000 | 0.0 | 0.0 | 0.9109 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9073 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9181 | 0.8460 | 0.9319 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6843 | 0.8430 | 0.0 | 0.6109 | 0.0795 | nan | 0.0000 | 0.0 | 0.0 | 0.7107 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5643 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7685 | 0.6944 | 0.8437 | 0.0 | 0.0 | 0.0 | 0.0 |
158
+ | 0.8797 | 1.7 | 680 | 0.8755 | 0.1797 | 0.2211 | 0.7946 | nan | 0.9228 | 0.9600 | 0.0 | 0.6712 | 0.0447 | nan | 0.0000 | 0.0 | 0.0 | 0.8878 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9058 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9313 | 0.8406 | 0.9120 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.7002 | 0.8299 | 0.0 | 0.5802 | 0.0434 | nan | 0.0000 | 0.0 | 0.0 | 0.7303 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5710 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7558 | 0.6902 | 0.8480 | 0.0 | 0.0 | 0.0 | 0.0 |
159
+ | 0.8329 | 1.75 | 700 | 0.8782 | 0.1802 | 0.2234 | 0.7910 | nan | 0.9567 | 0.9326 | 0.0 | 0.7030 | 0.0780 | nan | 0.0 | 0.0 | 0.0 | 0.8918 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9066 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9329 | 0.8216 | 0.9253 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6213 | 0.8476 | 0.0 | 0.6263 | 0.0752 | nan | 0.0 | 0.0 | 0.0 | 0.7226 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5718 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7541 | 0.6980 | 0.8500 | 0.0 | 0.0 | 0.0 | 0.0 |
160
+ | 0.8551 | 1.8 | 720 | 0.8607 | 0.1806 | 0.2231 | 0.7947 | nan | 0.9434 | 0.9503 | 0.0 | 0.6813 | 0.0720 | nan | 0.0000 | 0.0 | 0.0 | 0.8949 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9108 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9230 | 0.8410 | 0.9235 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6667 | 0.8402 | 0.0 | 0.6013 | 0.0691 | nan | 0.0000 | 0.0 | 0.0 | 0.7247 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5676 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7667 | 0.6951 | 0.8476 | 0.0 | 0.0 | 0.0 | 0.0 |
161
+ | 1.0606 | 1.85 | 740 | 0.8495 | 0.1805 | 0.2241 | 0.7945 | nan | 0.9486 | 0.9476 | 0.0 | 0.6721 | 0.0820 | nan | 0.0 | 0.0 | 0.0 | 0.9137 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9072 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9155 | 0.8497 | 0.9342 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6515 | 0.8446 | 0.0 | 0.6023 | 0.0786 | nan | 0.0 | 0.0 | 0.0 | 0.7120 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5703 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7725 | 0.6978 | 0.8463 | 0.0 | 0.0 | 0.0 | 0.0 |
162
+ | 0.875 | 1.9 | 760 | 0.8552 | 0.1819 | 0.2251 | 0.7966 | nan | 0.9384 | 0.9511 | 0.0 | 0.6797 | 0.1089 | nan | 0.0001 | 0.0 | 0.0 | 0.9089 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9078 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9227 | 0.8567 | 0.9292 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6766 | 0.8437 | 0.0 | 0.5987 | 0.1023 | nan | 0.0001 | 0.0 | 0.0 | 0.7202 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5687 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7672 | 0.6915 | 0.8501 | 0.0 | 0.0 | 0.0 | 0.0 |
163
+ | 1.1214 | 1.95 | 780 | 0.8541 | 0.1823 | 0.2254 | 0.7970 | nan | 0.9338 | 0.9521 | 0.0 | 0.6748 | 0.1255 | nan | 0.0002 | 0.0 | 0.0 | 0.9104 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9056 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9270 | 0.8590 | 0.9235 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6846 | 0.8435 | 0.0 | 0.5999 | 0.1174 | nan | 0.0002 | 0.0 | 0.0 | 0.7159 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5677 | 0.0 | 0.0001 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7634 | 0.6887 | 0.8506 | 0.0 | 0.0 | 0.0 | 0.0 |
164
+ | 0.8599 | 2.0 | 800 | 0.8640 | 0.1813 | 0.2233 | 0.7956 | nan | 0.9372 | 0.9555 | 0.0 | 0.6635 | 0.0799 | nan | 0.0001 | 0.0 | 0.0 | 0.8975 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9214 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9128 | 0.8493 | 0.9299 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.6819 | 0.8378 | 0.0 | 0.5970 | 0.0754 | nan | 0.0001 | 0.0 | 0.0 | 0.7287 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5594 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7763 | 0.6951 | 0.8496 | 0.0 | 0.0 | 0.0 | 0.0 |
165
 
166
 
167
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