Upload 15 files
Browse files- checkpoints/checkpoint_epoch_427.pth +3 -0
- config.toml +50 -0
- model_structure.txt +148 -0
- model_summary.txt +8 -0
- onnx_checkpoints/unet_dec_21_lsdb_only_epoch_427.onnx +3 -0
- segmentation_samples/sample_epoch_427_C107-3.pdf +0 -0
- segmentation_samples/sample_epoch_427_C53357.pdf +0 -0
- segmentation_samples/sample_epoch_427_C8-4.pdf +0 -0
- segmentation_samples/sample_epoch_600_C107-3.pdf +0 -0
- segmentation_samples/sample_epoch_600_C53357.pdf +0 -0
- segmentation_samples/sample_epoch_600_C8-4.pdf +0 -0
- time_log.txt +1 -0
- torchscript_checkpoints/unet_dec_21_lsdb_only_epoch_427.pt +3 -0
- training_logs/metric_plots.pdf +0 -0
- training_logs/training_stats.csv +601 -0
checkpoints/checkpoint_epoch_427.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:488a58978f600075ae731c462fc4f17e90517b88f8f5644275b5c7486a9fa204
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size 172059913
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config.toml
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experiment_name = "unet_dec_21_lsdb_only"
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base_dir = "/exports/csce/eddie/eng/groups/DunnGroup/matthew/models_gelgenie"
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[processing]
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base_hardware = "EDDIE"
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device = "GPU"
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pe = 1
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memory = 64
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[data]
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n_channels = 1
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batch_size = 2
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num_workers = 1
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val_percent = 10
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dir_train_mask = [ "/exports/csce/eddie/eng/groups/DunnGroup/matthew/gel_data/lsdb_gels/masks",]
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dir_train_img = [ "/exports/csce/eddie/eng/groups/DunnGroup/matthew/gel_data/lsdb_gels/images",]
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dir_val_img = [ "/exports/csce/eddie/eng/groups/DunnGroup/matthew/gel_data/lsdb_gels/val_images",]
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dir_val_mask = [ "/exports/csce/eddie/eng/groups/DunnGroup/matthew/gel_data/lsdb_gels/val_masks",]
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split_training_dataset = false
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apply_augmentations = true
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padding = true
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individual_padding = false
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weak_augmentations = false
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minmax_norm = false
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[model]
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model_name = "smp_unet"
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classes = 2
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in_channels = 1
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encoder_name = "resnet18"
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[training]
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loss = [ "dice", "crossentropy",]
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loss_component_weighting = [ 1, 1,]
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class_loss_weighting = false
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class_loss_weight_damper = [ 1.0, 1.0,]
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lr = 0.0001
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epochs = 600
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grad_scaler = true
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load_checkpoint = false
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optimizer_type = "adam"
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scheduler_type = "CosineAnnealingWarmRestarts"
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save_checkpoint = true
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checkpoint_frequency = 1
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wandb_track = true
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model_cleanup_frequency = 20
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wandb_id = "3etx3f9s"
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[training.scheduler_specs]
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restart_period = 100
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model_structure.txt
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======================================================================
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Layer (type:depth-idx) Param #
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======================================================================
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smp_UNet --
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├─ResNetEncoder: 1-1 --
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│ └─Conv2d: 2-1 3,136
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│ └─BatchNorm2d: 2-2 128
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│ └─ReLU: 2-3 --
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│ └─MaxPool2d: 2-4 --
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│ └─Sequential: 2-5 --
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│ │ └─BasicBlock: 3-1 --
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│ │ │ └─Conv2d: 4-1 36,864
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│ │ │ └─BatchNorm2d: 4-2 128
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│ │ │ └─ReLU: 4-3 --
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│ │ │ └─Conv2d: 4-4 36,864
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│ │ │ └─BatchNorm2d: 4-5 128
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│ │ └─BasicBlock: 3-2 --
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│ │ │ └─Conv2d: 4-6 36,864
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│ │ │ └─BatchNorm2d: 4-7 128
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│ │ │ └─ReLU: 4-8 --
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│ │ │ └─Conv2d: 4-9 36,864
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│ │ │ └─BatchNorm2d: 4-10 128
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│ └─Sequential: 2-6 --
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│ │ └─BasicBlock: 3-3 --
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│ │ │ └─Conv2d: 4-11 73,728
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│ │ │ └─BatchNorm2d: 4-12 256
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│ │ │ └─ReLU: 4-13 --
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│ │ │ └─Conv2d: 4-14 147,456
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│ │ │ └─BatchNorm2d: 4-15 256
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│ │ │ └─Sequential: 4-16 --
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│ │ │ │ └─Conv2d: 5-1 8,192
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│ │ │ │ └─BatchNorm2d: 5-2 256
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│ │ └─BasicBlock: 3-4 --
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│ │ │ └─Conv2d: 4-17 147,456
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│ │ │ └─BatchNorm2d: 4-18 256
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│ │ │ └─ReLU: 4-19 --
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│ │ │ └─Conv2d: 4-20 147,456
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│ │ │ └─BatchNorm2d: 4-21 256
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│ └─Sequential: 2-7 --
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│ │ └─BasicBlock: 3-5 --
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│ │ │ └─Conv2d: 4-22 294,912
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│ │ │ └─BatchNorm2d: 4-23 512
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│ │ │ └─ReLU: 4-24 --
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│ │ │ └─Conv2d: 4-25 589,824
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│ │ │ └─BatchNorm2d: 4-26 512
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│ │ │ └─Sequential: 4-27 --
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│ │ │ │ └─Conv2d: 5-3 32,768
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│ │ │ │ └─BatchNorm2d: 5-4 512
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│ │ └─BasicBlock: 3-6 --
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│ │ │ └─Conv2d: 4-28 589,824
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│ │ │ └─BatchNorm2d: 4-29 512
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│ │ │ └─ReLU: 4-30 --
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│ │ │ └─Conv2d: 4-31 589,824
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│ │ │ └─BatchNorm2d: 4-32 512
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│ └─Sequential: 2-8 --
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│ │ └─BasicBlock: 3-7 --
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│ │ │ └─Conv2d: 4-33 1,179,648
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│ │ │ └─BatchNorm2d: 4-34 1,024
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│ │ │ └─ReLU: 4-35 --
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│ │ │ └─Conv2d: 4-36 2,359,296
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│ │ │ └─BatchNorm2d: 4-37 1,024
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│ │ │ └─Sequential: 4-38 --
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│ │ │ │ └─Conv2d: 5-5 131,072
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│ │ │ │ └─BatchNorm2d: 5-6 1,024
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│ │ └─BasicBlock: 3-8 --
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│ │ │ └─Conv2d: 4-39 2,359,296
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│ │ │ └─BatchNorm2d: 4-40 1,024
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│ │ │ └─ReLU: 4-41 --
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│ │ │ └─Conv2d: 4-42 2,359,296
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│ │ │ └─BatchNorm2d: 4-43 1,024
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├─UnetDecoder: 1-2 --
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│ └─Identity: 2-9 --
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│ └─ModuleList: 2-10 --
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│ │ └─DecoderBlock: 3-9 --
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│ │ │ └─Conv2dReLU: 4-44 --
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│ │ │ │ └─Conv2d: 5-7 1,769,472
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│ │ │ │ └─BatchNorm2d: 5-8 512
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│ │ │ │ └─ReLU: 5-9 --
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│ │ │ └─Attention: 4-45 --
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│ │ │ │ └─Identity: 5-10 --
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│ │ │ └─Conv2dReLU: 4-46 --
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│ │ │ │ └─Conv2d: 5-11 589,824
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│ │ │ │ └─BatchNorm2d: 5-12 512
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│ │ �� │ └─ReLU: 5-13 --
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│ │ │ └─Attention: 4-47 --
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│ │ │ │ └─Identity: 5-14 --
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│ │ └─DecoderBlock: 3-10 --
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│ │ │ └─Conv2dReLU: 4-48 --
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│ │ │ │ └─Conv2d: 5-15 442,368
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│ │ │ │ └─BatchNorm2d: 5-16 256
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│ │ │ │ └─ReLU: 5-17 --
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│ │ │ └─Attention: 4-49 --
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│ │ │ │ └─Identity: 5-18 --
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│ │ │ └─Conv2dReLU: 4-50 --
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│ │ │ │ └─Conv2d: 5-19 147,456
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│ │ │ │ └─BatchNorm2d: 5-20 256
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│ │ │ │ └─ReLU: 5-21 --
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│ │ │ └─Attention: 4-51 --
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│ │ │ │ └─Identity: 5-22 --
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│ │ └─DecoderBlock: 3-11 --
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│ │ │ └─Conv2dReLU: 4-52 --
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│ │ │ │ └─Conv2d: 5-23 110,592
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│ │ │ │ └─BatchNorm2d: 5-24 128
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│ │ │ │ └─ReLU: 5-25 --
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│ │ │ └─Attention: 4-53 --
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│ │ │ │ └─Identity: 5-26 --
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│ │ │ └─Conv2dReLU: 4-54 --
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│ │ │ │ └─Conv2d: 5-27 36,864
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│ │ │ │ └─BatchNorm2d: 5-28 128
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│ │ │ │ └─ReLU: 5-29 --
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│ │ │ └─Attention: 4-55 --
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│ │ │ │ └─Identity: 5-30 --
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│ │ └─DecoderBlock: 3-12 --
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│ │ │ └─Conv2dReLU: 4-56 --
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115 |
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│ │ │ │ └─Conv2d: 5-31 36,864
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│ │ │ │ └─BatchNorm2d: 5-32 64
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│ │ │ │ └─ReLU: 5-33 --
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│ │ │ └─Attention: 4-57 --
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119 |
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│ │ │ │ └─Identity: 5-34 --
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│ │ │ └─Conv2dReLU: 4-58 --
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│ │ │ │ └─Conv2d: 5-35 9,216
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│ │ │ │ └─BatchNorm2d: 5-36 64
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│ │ │ │ └─ReLU: 5-37 --
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│ │ │ └─Attention: 4-59 --
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125 |
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│ │ │ │ └─Identity: 5-38 --
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126 |
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│ │ └─DecoderBlock: 3-13 --
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│ │ │ └─Conv2dReLU: 4-60 --
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128 |
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│ │ │ │ └─Conv2d: 5-39 4,608
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│ │ │ │ └─BatchNorm2d: 5-40 32
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│ │ │ │ └─ReLU: 5-41 --
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│ │ │ └─Attention: 4-61 --
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132 |
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│ │ │ │ └─Identity: 5-42 --
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│ │ │ └─Conv2dReLU: 4-62 --
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134 |
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│ │ │ │ └─Conv2d: 5-43 2,304
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135 |
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│ │ │ │ └─BatchNorm2d: 5-44 32
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136 |
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│ │ │ │ └─ReLU: 5-45 --
|
137 |
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│ │ │ └─Attention: 4-63 --
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138 |
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│ │ │ │ └─Identity: 5-46 --
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├─SegmentationHead: 1-3 --
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│ └─Conv2d: 2-11 290
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│ └─Identity: 2-12 --
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142 |
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│ └─Activation: 2-13 --
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143 |
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│ │ └─Identity: 3-14 --
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======================================================================
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145 |
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Total params: 14,322,082
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Trainable params: 14,322,082
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Non-trainable params: 0
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======================================================================
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model_summary.txt
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Model Summary
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┏━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┓
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┃ Parameter ┃ Value ┃
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┡━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩
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│ Network │ smp_unet │
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│ Trainable Parameters │ 14322082 │
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│ Output channels │ 2 │
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└──────────────────────┴──────────┘
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onnx_checkpoints/unet_dec_21_lsdb_only_epoch_427.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:19a1d71cfdc64fcefa3f7d141afe3b8defeeb9a587e00f5a67255b762e483f0c
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size 57279486
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segmentation_samples/sample_epoch_427_C107-3.pdf
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segmentation_samples/sample_epoch_427_C53357.pdf
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segmentation_samples/sample_epoch_427_C8-4.pdf
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segmentation_samples/sample_epoch_600_C107-3.pdf
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segmentation_samples/sample_epoch_600_C53357.pdf
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segmentation_samples/sample_epoch_600_C8-4.pdf
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time_log.txt
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Time initiated first training run: 2023_12_21_23;17;26
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torchscript_checkpoints/unet_dec_21_lsdb_only_epoch_427.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:209b504ada27cbfbaa242ae885a32ef2b811f2104b824c44232338aea64efe56
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size 57602262
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training_logs/metric_plots.pdf
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training_logs/training_stats.csv
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|
1 |
+
Dice Loss,Cross-Entropy Loss,Training Loss,Learning Rate,Dice Score,Epoch
|
2 |
+
0.605761848114155,0.5059882612140091,1.1117501038092155,0.0001,0.09739130673309167,1
|
3 |
+
0.5551469016958166,0.3264452605335801,0.8815921589180276,9.99753526902683e-05,0.2531959228217602,2
|
4 |
+
0.5251907860791242,0.2309947654053017,0.7561855603147436,9.990143508499217e-05,0.4166782697041829,3
|
5 |
+
0.5055128115194815,0.17589025806497643,0.6814030629617197,9.977832013192385e-05,0.4230249499281247,4
|
6 |
+
0.49077980165128354,0.14050545764190178,0.6312852656399762,9.960612933065818e-05,0.5309478938579559,5
|
7 |
+
0.47779200032905295,0.1137579850576542,0.5915499837310226,9.938503261272713e-05,0.5612431317567825,6
|
8 |
+
0.4621845240946169,0.09524334222078323,0.5574278654875578,9.9115248173898e-05,0.5796806911627451,7
|
9 |
+
0.4415741408312762,0.07992307786588315,0.5214972231123183,9.879704225884044e-05,0.6362427175045013,8
|
10 |
+
0.4287151716373585,0.0691170499280647,0.4978322188059489,9.843072889837513e-05,0.5487521241108576,9
|
11 |
+
0.4196764009970206,0.05782924606292336,0.47750564526628564,9.801666959956331e-05,0.676877756913503,10
|
12 |
+
0.40885768996344674,0.050008517034627775,0.45886620437657394,9.755527298894293e-05,0.7006322542826334,11
|
13 |
+
0.3834126348848696,0.04375059212799425,0.427163224529337,9.704699440926357e-05,0.6871516505877177,12
|
14 |
+
0.37671659610889574,0.03896052921535792,0.4156771258071617,9.649233547011815e-05,0.6854060888290405,13
|
15 |
+
0.3622411180425573,0.037954595077920844,0.4001957122926359,9.589184355291485e-05,0.6887711385885874,14
|
16 |
+
0.34570053771690085,0.030123832394127494,0.37582436866230434,9.524611127067768e-05,0.7181382775306702,15
|
17 |
+
0.33394198064450864,0.02836166915518266,0.36230365104145473,9.455577588320898e-05,0.6829356749852499,16
|
18 |
+
0.29002858974315504,0.024016557744255772,0.31404514886714796,9.382151866819098e-05,0.6809627910455068,17
|
19 |
+
0.28917587024194225,0.021772746548608498,0.310948618584209,9.304406424884699e-05,0.7189399202664694,18
|
20 |
+
0.2604466919545774,0.022180913844042353,0.2826276073853175,9.222417987882565e-05,0.6863855421543121,19
|
21 |
+
0.2477565297374019,0.020484034903347492,0.2682405627436108,9.136267468501436e-05,0.7182878454526266,20
|
22 |
+
0.2434945128582142,0.021349970423788937,0.26484448103993025,9.046039886902862e-05,0.7218596537907919,21
|
23 |
+
0.23660099947894062,0.02066631373707895,0.2572673123191904,8.951824286816573e-05,0.670687347650528,22
|
24 |
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0.218953980339898,0.018376694060862064,0.2373306745732272,8.853713647665068e-05,0.7231861054897308,23
|
25 |
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0.21646877350630583,0.01904605604984142,0.2355148317637267,8.751804792804146e-05,0.6551052729288737,24
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26 |
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0.22752744842458655,0.018475258912615204,0.24600270611268502,8.646198293969951e-05,0.6989699800809225,25
|
27 |
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0.20329209831025866,0.017310811706853134,0.22060291082770736,8.536998372026805e-05,0.7073431015014648,26
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28 |
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0.19693009720908272,0.018034574713695933,0.2149646723711932,8.4243127941138e-05,0.713415135939916,27
|
29 |
+
0.18678696950276694,0.016994693885660835,0.20378166354364818,8.308252767291642e-05,0.7294531663258871,28
|
30 |
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0.18352017137739393,0.016406146447277732,0.19992631756597096,8.188932828794705e-05,0.7150114377339681,29
|
31 |
+
0.1861167969527068,0.01678126734784908,0.2028980644212829,8.066470732996619e-05,0.7473182380199432,30
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32 |
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0.17215857903162637,0.015645915366433286,0.18780449391515167,7.940987335200905e-05,0.7711592316627502,31
|
33 |
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0.18065773336975663,0.01641977323150193,0.19707750529050827,7.812606472371394e-05,0.69810684521993,32
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34 |
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0.176227573995237,0.016125664873807517,0.19235323948992622,7.681454840920088e-05,0.7438644369443258,33
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35 |
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0.16579979878884774,0.017246165519787207,0.18304596455008895,7.547661871673105e-05,0.7134006023406982,34
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36 |
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0.16253364306909066,0.016972988826671132,0.1795066319130085,7.411359602138067e-05,0.705499549706777,35
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37 |
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0.16184189584520128,0.017069742359496928,0.1789116390325405,7.272682546199037e-05,0.7403889298439026,36
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38 |
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0.16241730142522742,0.017132927629130858,0.17955023050308228,7.131767561367538e-05,0.7890664637088776,37
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39 |
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0.15401188532511392,0.016065658846249182,0.17007754494746527,6.988753713720729e-05,0.7319493989149729,38
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40 |
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0.17059431473414102,0.017766947582088136,0.18836126338552545,6.843782140659968e-05,0.7471041480700175,39
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41 |
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0.15136491810833966,0.016149657709455048,0.16751457612823556,6.696995911625232e-05,0.7466817100842794,40
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42 |
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0.15671824746661717,0.016162193276815943,0.17288044067444625,6.548539886902863e-05,0.7744553486506144,41
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43 |
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0.1593908115669533,0.01732527085200504,0.1767160823499715,6.398560574665952e-05,0.7462842166423798,42
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44 |
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0.15404202540715536,0.01569889887684473,0.1697409244047271,6.247205986388449e-05,0.752243439356486,43
|
45 |
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0.13519517359910188,0.014417156646097148,0.14961233155594933,6.094625490775731e-05,0.7413167059421539,44
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46 |
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0.15127247130429303,0.016808895773633762,0.16808136773330193,5.940969666355696e-05,0.7427932620048523,45
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47 |
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0.14760239035994918,0.016733749424693762,0.16433614078495237,5.786390152875954e-05,0.746228943268458,46
|
48 |
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0.14328656373200593,0.014811323576227383,0.15809788830854274,5.631039501653701e-05,0.7468872964382172,47
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49 |
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0.13859261406792533,0.016602366904003754,0.1551949820584721,5.475071025025979e-05,0.744477391242981,48
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50 |
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0.14426894099624069,0.015437417939581253,0.15970635800449937,5.318638645048921e-05,0.7587981621424357,49
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51 |
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0.1456613960089507,0.016556214506703394,0.16221760986027894,5.1618967415952515e-05,0.7597609261671702,50
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52 |
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0.14644995221385249,0.01665949507581967,0.16310944766909988,5.0050000000000004e-05,0.7255222499370575,51
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53 |
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0.13073267097826358,0.014737746238501536,0.14547041803598404,4.848103258404749e-05,0.7351567049821218,52
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54 |
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0.13031797276602852,0.014771438583179756,0.14508941052136598,4.69136135495108e-05,0.7554379403591156,53
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55 |
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0.13312149930883338,0.014349983884366575,0.14747148227912407,4.5349289749740215e-05,0.7387095391750336,54
|
56 |
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0.13295123753724275,0.015931731443507253,0.14888296883415292,4.378960498346301e-05,0.741974393526713,55
|
57 |
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0.14492843769214772,0.01698655478173384,0.16191499321549027,4.223609847124047e-05,0.7381592293580373,56
|
58 |
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0.12672238438217728,0.015119536271042846,0.1418419204376362,4.069030333644306e-05,0.7506756087144216,57
|
59 |
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0.13205575501477276,0.016435693664890196,0.14849144910220746,3.9153745092242715e-05,0.736892173687617,58
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60 |
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0.13262124635555125,0.013480000680795422,0.14610124655343867,3.7627940136115507e-05,0.755760004123052,59
|
61 |
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0.13104651813153867,0.01410697354003787,0.1451534899296584,3.6114394253340505e-05,0.7578226427237192,60
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62 |
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0.13788970752998633,0.015157994624503233,0.15304770293059172,3.4614601130971394e-05,0.7356012562910715,61
|
63 |
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0.15190384123060438,0.017059740644914133,0.1689635807717288,3.31300408837477e-05,0.7605931063493093,62
|
64 |
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0.14404648100888287,0.018864534898764558,0.16291101525227228,3.166217859340035e-05,0.7381340265274048,63
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65 |
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0.14630406653439557,0.0183994531010588,0.16470351898007923,3.0212462862792702e-05,0.7483782172203064,64
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66 |
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0.13112356706901832,0.015601024721507673,0.14672459054876258,2.8782324386324622e-05,0.7450461288293203,65
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67 |
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0.11875723688690751,0.012287398817500583,0.13104463589412194,2.737317453800964e-05,0.751253068447113,66
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68 |
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0.1254293410866349,0.01394012178880749,0.1393694626512351,2.5986403978619313e-05,0.7646563053131104,67
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69 |
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0.14913074175516763,0.01745008294367128,0.16658082521624035,2.4623381283268953e-05,0.7443379362424215,68
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70 |
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0.13035620362670333,0.01461532160087868,0.14497152550352943,2.3285451590799106e-05,0.7600368857383728,69
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71 |
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0.12034436508461281,0.012704714080663744,0.13304907911353642,2.1973935276286073e-05,0.7543948988119761,70
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72 |
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0.13448977028882061,0.015577674343216198,0.15006744420086895,2.069012664799097e-05,0.7445942362149557,71
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73 |
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0.1313510956587615,0.014904624713515793,0.14625572082069185,1.9435292670033817e-05,0.739799420038859,72
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74 |
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0.1343120535214742,0.015281457833393856,0.14959351000962434,1.8210671712052947e-05,0.7523718774318695,73
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75 |
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0.13529231150945029,0.017523749765974504,0.15281606244820137,1.7017472327083596e-05,0.7548030912876129,74
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