Organiza tus páginas con colecciones
Guarda y categoriza el contenido según tus preferencias.
Como científico de datos, este un flujo de trabajo común: entrenar un modelo de forma local (en mi notebook), registrar los parámetros, registrar las métricas de serie temporal de entrenamiento en Vertex AI TensorBoard y registrar las métricas de evaluación.
Puedes ver las ejecuciones del experimento asociadas con un experimento en la página de experimentos en la consola de Google Cloud .
Notebook: Compara modelos entrenados de forma local
En el notebook “Vertex AI: haz un seguimiento de los parámetros y las métricas de los modelos entrenados de forma local”, aprenderás a usar Vertex AI Experiments para realizar las siguientes tareas:
Registra los parámetros del modelo.
Registra la pérdida y las métricas en cada ciclo de entrenamiento en TensorBoard.
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-09-04 (UTC)"],[],[],null,["# Compare trained and evaluated models: Notebook\n\nAs a Data Scientist, this is a common workflow: Train a model\nlocally (in my Notebook), log the parameters, log the training time series\nmetrics to ,\nand log the evaluation metrics.\n\nYou can view the experiment runs associated with an experiment on the\nexperiments page in the Google Cloud console.\n\nNotebook: Compare locally trained models\n----------------------------------------\n\n| To see an example of comparing models,\n| run the \"Vertex AI: Track parameters and metrics for locally trained models\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/experiments/comparing_local_trained_models.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fexperiments%2Fcomparing_local_trained_models.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fexperiments%2Fcomparing_local_trained_models.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/experiments/comparing_local_trained_models.ipynb)\n\nIn the \"Vertex AI: Track parameters and metrics for locally trained\nmodels\" notebook, you'll learn how to use Vertex AI Experiments to:\n\n- Log the model parameters.\n- Log the loss and metrics on every epoch to TensorBoard.\n- Log the evaluation metrics.\n- Compare two experiment runs.\n\nRelevant content\n----------------\n\n- [Log data to an experiment run](/vertex-ai/docs/experiments/log-data)\n - [Assign backing Vertex AI TensorBoard resource for Time Series Metric](/vertex-ai/docs/experiments/log-data#assign_backing_resource_for_time_series_metric)\n - [Log summary metrics](/vertex-ai/docs/experiments/log-data#summary_metrics)\n - [Log time series metrics](/vertex-ai/docs/experiments/log-data#time_series_metrics)\n - [Log parameters](/vertex-ai/docs/experiments/log-data#parameters)"]]