Added Pt Train Model node to allow specifying a Loss node for training.
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| [Pt Predict Regression Model](pt_predict_regression_model.md) | Performs inference on input data. |
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| [Pt Train Classification Model](pt_train_classification_model.md) | Trains a classification model using a given dataset, optimizer, and number of epochs. |
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| [Pt Train Classification Model Lr](pt_train_classification_model_lr.md) | Trains a classification model using a given dataset, optimizer, and number of epochs with learning rate decay. |
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| [Pt Train Model](pt_train_model.md) | Trains a model using a given dataset, loss function, optimizer, and number of epochs with learning rate decay. |
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| [Pt Train Regression Model](pt_train_regression_model.md) | Trains a regression model using a given dataset, optimizer, and number of epochs. |
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| [Pto Lr Scheduler Cosine Annealing](pto_lr_scheduler_cosine_annealing.md) | Creates a cosine annealing learning rate scheduler for an optimizer. |
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| [Pto Lr Scheduler Reduce On Plateau](pto_lr_scheduler_reduce_on_plateau.md) | Creates a reduce-on-plateau learning rate scheduler for an optimizer. |
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# Pt Train Model
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Trains a model using a given dataset, loss function, optimizer, and number of epochs with learning rate decay.
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early_stopping_rounds: Specifies the number of rounds to monitor the evaluation loss when early_stopping is enabled and validation data is specified. If the loss does not decrease compared to the current best loss within this period, training will be stopped.
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output_best_val_model: Whether to outputs the model with the best val loss or the model from the last epoch.
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Functionality-wise, this node is identical with PtTrainClassificationModelLr except that you can specify a custom loss function in this model where PtTrainClassificationModelLr uses nn.CrossEntropyLoss().
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## Input
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| Name | Data type |
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|---|---|
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| model | Ptmodel |
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| train_loader | Ptdataloader |
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| optimizer | Ptoptimizer |
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| loss_function | Ptloss |
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| epochs | Int |
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| use_gpu | Boolean |
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| early_stopping | Boolean |
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| early_stopping_rounds | Int |
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| output_best_val_model | Boolean |
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| scheduler | Ptlrscheduler |
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| val_loader | Ptdataloader |
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## Output
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| Data type |
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|---|
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| Ptmodel |
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| Tensor |
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| Tensor |
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<HR>
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Category: PyTorch wrapper - Training
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ComfyUI Pt Wrapper Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
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