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Expose early stopping hyper-parameters for all tasks (#1241)
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-32
lines changed

20 files changed

+478
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‎QUICK_START_GUIDE.md

+19
Original file line numberDiff line numberDiff line change
@@ -173,6 +173,9 @@ usage: ote train template params [-h]
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[--learning_parameters.learning_rate LEARNING_RATE]
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[--learning_parameters.learning_rate_warmup_iters LEARNING_RATE_WARMUP_ITERS]
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[--learning_parameters.num_iters NUM_ITERS]
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[--learning_parameters.enable_early_stopping ENABLE_EARLY_STOPPING]
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[--learning_parameters.early_stop_patience EARLY_STOP_PATIENCE]
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[--learning_parameters.early_stop_iteration_patience EARLY_STOP_ITERATION_PATIENCE]
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[--postprocessing.confidence_threshold CONFIDENCE_THRESHOLD]
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[--postprocessing.result_based_confidence_threshold RESULT_BASED_CONFIDENCE_THRESHOLD]
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[--nncf_optimization.enable_quantization ENABLE_QUANTIZATION]
@@ -205,6 +208,22 @@ optional arguments:
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default_value: 300
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max_value: 100000
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min_value: 1
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--learning_parameters.enable_early_stopping ENABLE_EARLY_STOPPING
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header: Enable early stopping of the training
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type: BOOLEAN
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default_value: True
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--learning_parameters.early_stop_patience EARLY_STOP_PATIENCE
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header: Patience for early stopping
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type: INTEGER
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default_value: 10
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max_value: 50
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min_value: 0
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--learning_parameters.early_stop_iteration_patience EARLY_STOP_ITERATION_PATIENCE
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header: Iteration patience for early stopping
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type: INTEGER
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default_value: 0
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max_value: 1000
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min_value: 0
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--postprocessing.confidence_threshold CONFIDENCE_THRESHOLD
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header: Confidence threshold
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type: FLOAT

‎external/model-preparation-algorithm/configs/classification/configuration.yaml

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@@ -121,17 +121,68 @@ learning_parameters:
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enable_early_stopping:
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affects_outcome_of: TRAINING
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default_value: true
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description: Adaptive early exit from training when accuracy isn't changed or decreased for several epochs.
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description: Early exit from training when validation accuracy isn't changed or decreased for several epochs.
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editable: true
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header: Enable adaptive early stopping of the training
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header: Enable early stopping of the training
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type: BOOLEAN
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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visible_in_ui: false
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visible_in_ui: true
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warning: null
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early_stop_start:
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affects_outcome_of: TRAINING
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default_value: 3
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editable: true
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header: Start epoch for early stopping
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max_value: 1000
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 3
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visible_in_ui: false
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early_stop_patience:
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affects_outcome_of: TRAINING
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default_value: 8
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description: Training will stop if the model does not improve within the number of epochs of patience.
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editable: true
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header: Patience for early stopping
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max_value: 50
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 8
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visible_in_ui: true
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warning: This is applied exclusively when early stopping is enabled.
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early_stop_iteration_patience:
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affects_outcome_of: TRAINING
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default_value: 0
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description:
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Training will stop if the model does not improve within the number of iterations of patience.
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This ensures the model is trained enough with the number of iterations of patience before early stopping.
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editable: true
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header: Iteration patience for early stopping
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max_value: 1000
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 0
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visible_in_ui: true
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warning: This is applied exclusively when early stopping is enabled.
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type: PARAMETER_GROUP
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visible_in_ui: true
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pot_parameters:

‎external/model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/hpo_config.yaml

+3-3
Original file line numberDiff line numberDiff line change
@@ -4,9 +4,9 @@ hp_space:
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learning_parameters.learning_rate:
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param_type: qloguniform
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range:
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- 0.0014
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- 0.035
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- 0.0001
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- 0.00098
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- 0.0245
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- 0.00001
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learning_parameters.batch_size:
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param_type: qloguniform
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range:

‎external/model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/model.py

-1
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@@ -2,5 +2,4 @@
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'../../../submodule/models/classification/ote_efficientnet_b0.yaml',
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]
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5-
runner = dict(max_epochs=20)
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fp16 = dict(loss_scale=512.)

‎external/model-preparation-algorithm/configs/classification/efficientnet_b0_cls_incr/template.yaml

+1-1
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@@ -32,7 +32,7 @@ hyper_parameters:
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num_workers:
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default_value: 0
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learning_rate:
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default_value: 0.007
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default_value: 0.0049
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auto_hpo_state: POSSIBLE
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learning_rate_warmup_iters:
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default_value: 0

‎external/model-preparation-algorithm/configs/classification/efficientnet_v2_s_cls_incr/model.py

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@@ -2,5 +2,4 @@
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'../../../submodule/models/classification/ote_efficientnet_v2_s.yaml',
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]
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5-
runner = dict(max_epochs=20)
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fp16 = dict(loss_scale=512.)

‎external/model-preparation-algorithm/configs/classification/efficientnet_v2_s_cls_incr/template.yaml

+1-1
Original file line numberDiff line numberDiff line change
@@ -32,7 +32,7 @@ hyper_parameters:
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num_workers:
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default_value: 0
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learning_rate:
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default_value: 0.007
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default_value: 0.0071
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auto_hpo_state: POSSIBLE
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learning_rate_warmup_iters:
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default_value: 0

‎external/model-preparation-algorithm/configs/classification/mobilenet_v3_large_1_cls_incr/hpo_config.yaml

+2-2
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@@ -4,9 +4,9 @@ hp_space:
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learning_parameters.learning_rate:
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param_type: qloguniform
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range:
7-
- 0.0008
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- 0.00029
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- 0.1
9-
- 0.0001
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- 0.00001
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learning_parameters.batch_size:
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param_type: qloguniform
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range:

‎external/model-preparation-algorithm/configs/classification/mobilenet_v3_large_1_cls_incr/model.py

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@@ -2,5 +2,4 @@
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'../../../submodule/models/classification/ote_mobilenet_v3_large.yaml',
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]
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5-
runner = dict(max_epochs=20)
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fp16 = dict(loss_scale=512.)

‎external/model-preparation-algorithm/configs/classification/mobilenet_v3_large_1_cls_incr/template.yaml

+2-2
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@@ -32,10 +32,10 @@ hyper_parameters:
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num_workers:
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default_value: 0
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learning_rate:
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default_value: 0.016
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default_value: 0.0058
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auto_hpo_state: POSSIBLE
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learning_rate_warmup_iters:
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default_value: 100
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default_value: 10
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num_iters:
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default_value: 90
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nncf_optimization:

‎external/model-preparation-algorithm/configs/detection/configuration.yaml

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@@ -119,6 +119,85 @@ learning_parameters:
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value: 0
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visible_in_ui: true
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warning: null
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enable_early_stopping:
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affects_outcome_of: TRAINING
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default_value: true
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description: Early exit from training when validation accuracy isn't changed or decreased for several epochs.
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editable: true
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header: Enable early stopping of the training
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type: BOOLEAN
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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visible_in_ui: true
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warning: null
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early_stop_start:
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affects_outcome_of: TRAINING
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default_value: 3
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editable: true
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header: Start epoch for early stopping
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max_value: 1000
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 3
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visible_in_ui: false
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early_stop_patience:
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affects_outcome_of: TRAINING
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default_value: 10
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description: Training will stop if the model does not improve within the number of epochs of patience.
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editable: true
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header: Patience for early stopping
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max_value: 50
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min_value: 0
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type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 10
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visible_in_ui: true
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warning: This is applied exclusively when early stopping is enabled.
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early_stop_iteration_patience:
169+
affects_outcome_of: TRAINING
170+
default_value: 0
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description:
172+
Training will stop if the model does not improve within the number of iterations of patience.
173+
This ensures the model is trained enough with the number of iterations of patience before early stopping.
174+
editable: true
175+
header: Iteration patience for early stopping
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max_value: 1000
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min_value: 0
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type: INTEGER
179+
ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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value: 0
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visible_in_ui: true
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warning: This is applied exclusively when early stopping is enabled.
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use_adaptive_interval:
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affects_outcome_of: TRAINING
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default_value: true
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description: Depending on the size of iteration per epoch, adaptively update the validation interval and related values.
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editable: true
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header: Use adaptive validation interval
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type: BOOLEAN
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
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rules: []
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type: UI_RULES
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visible_in_ui: true
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warning: This will automatically control the patience and interval when early stopping is enabled.
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type: PARAMETER_GROUP
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visible_in_ui: true
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postprocessing:

‎external/model-preparation-algorithm/configs/instance-segmentation/configuration.yaml

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@@ -119,6 +119,85 @@ learning_parameters:
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value: 0
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visible_in_ui: true
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warning: null
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enable_early_stopping:
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affects_outcome_of: TRAINING
124+
default_value: true
125+
description: Early exit from training when validation accuracy isn't changed or decreased for several epochs.
126+
editable: true
127+
header: Enable early stopping of the training
128+
type: BOOLEAN
129+
ui_rules:
130+
action: DISABLE_EDITING
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operator: AND
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rules: []
133+
type: UI_RULES
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visible_in_ui: true
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warning: null
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early_stop_start:
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affects_outcome_of: TRAINING
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default_value: 3
139+
editable: true
140+
header: Start epoch for early stopping
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max_value: 1000
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min_value: 0
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type: INTEGER
144+
ui_rules:
145+
action: DISABLE_EDITING
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operator: AND
147+
rules: []
148+
type: UI_RULES
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value: 3
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visible_in_ui: false
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early_stop_patience:
152+
affects_outcome_of: TRAINING
153+
default_value: 10
154+
description: Training will stop if the model does not improve within the number of epochs of patience.
155+
editable: true
156+
header: Patience for early stopping
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max_value: 50
158+
min_value: 0
159+
type: INTEGER
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ui_rules:
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action: DISABLE_EDITING
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operator: AND
163+
rules: []
164+
type: UI_RULES
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value: 10
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visible_in_ui: true
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warning: This is applied exclusively when early stopping is enabled.
168+
early_stop_iteration_patience:
169+
affects_outcome_of: TRAINING
170+
default_value: 0
171+
description:
172+
Training will stop if the model does not improve within the number of iterations of patience.
173+
This ensures the model is trained enough with the number of iterations of patience before early stopping.
174+
editable: true
175+
header: Iteration patience for early stopping
176+
max_value: 1000
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min_value: 0
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type: INTEGER
179+
ui_rules:
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action: DISABLE_EDITING
181+
operator: AND
182+
rules: []
183+
type: UI_RULES
184+
value: 0
185+
visible_in_ui: true
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warning: This is applied exclusively when early stopping is enabled.
187+
use_adaptive_interval:
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affects_outcome_of: TRAINING
189+
default_value: true
190+
description: Depending on the size of iteration per epoch, adaptively update the validation interval and related values.
191+
editable: true
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header: Use adaptive validation interval
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type: BOOLEAN
194+
ui_rules:
195+
action: DISABLE_EDITING
196+
operator: AND
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rules: []
198+
type: UI_RULES
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visible_in_ui: true
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warning: This will automatically control the patience and interval when early stopping is enabled.
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type: PARAMETER_GROUP
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visible_in_ui: true
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postprocessing:

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