Previousmodel

Previousmodel is a label used in documentation and tooling to refer to the model that preceded the currently active or deployed model in a sequence. It is a conceptual reference point in contexts such as machine learning pipelines, software release processes, and experimentation logs.

In model versioning and deployment, each new model version is identified in a way that makes the immediately prior version identifiable as previousmodel. This enables rollback, side-by-side evaluation, and traceability of changes. Systems often store previousmodel information in a model registry or metadata store, including artifacts such as weights, training data snapshots, hyperparameters, and evaluation metrics.

During decision making, teams compare the current model against previousmodel using standardized metrics and benchmarks. Common metrics include accuracy, precision and recall, F1 score, latency, throughput, and resource usage. These comparisons inform deployment choices, A/B testing outcomes, and performance validation before promoting a model to production.

Examples of use include baselining in A/B testing, where previousmodel serves as the baseline for comparison, and in continuous deployment workflows, where a fallback to previousmodel may be triggered if the new model underperforms or introduces regressions. In multi-branch experimentation, multiple predecessors may exist, making explicit semantics for which version constitutes previousmodel essential for clarity.

See also: model versioning, model registry, currentmodel, rollback, artifact store, experiment tracking.