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Added lr scheduler nodes and cifar10 workflows.

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HowToSD
2025-03-12 14:57:44 -07:00
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docs/reference/pt_train_classification_model_lr.md
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# Pt Train Classification Model Lr
Trains a classification model using a given dataset, optimizer, and number of epochs with learning rate decay.
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.
output_best_val_model: Whether to outputs the model with the best val loss or the model from the last epoch.
## Input
| Name | Data type |
|---|---|
| model | Ptmodel |
| train_loader | Ptdataloader |
| optimizer | Ptoptimizer |
| scheduler | Ptlrscheduler |
| epochs | Int |
| use_gpu | Boolean |
| early_stopping | Boolean |
| early_stopping_rounds | Int |
| output_best_val_model | Boolean |
| val_loader | Ptdataloader |
## Output
| Data type |
|---|
| Ptmodel |
| Tensor |
| Tensor |
<HR>
Category: PyTorch wrapper - Training
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.