All notable changes to this project are documented in this file.
0.2.0 - 2026-06-23
Added
- Added model version 7,
:conservative_cnn, a conservative CNN architecture intended to reduce false positives. - Added false-positive-aware validation scoring for checkpoint selection and hyperparameter tuning.
- Added threshold calibration for v7, including persisted
decision_policymetadata in serialized classifiers. - Added v7 inference safeguards for low-signal inputs through configurable positive thresholds and minimum positive token counts.
Changed
- Changed the default training model to v7,
:conservative_cnn. - Changed the default vector length to
512. - Updated serialization, loading, serving, and compiled prediction paths to reuse persisted decision policies when available.
Documentation
- Updated README and generated documentation sources for v7, threshold calibration, production guidance, model versions, and the
0.2.0dependency snippet.
0.1.3 - 2026-06-15
Added
- Added model version 6,
:transformer, with sequence-length logit bias for short or missing text inputs. - Added static sinusoidal positional embeddings to the transformer model.
- Added transformer execution and logit-bias tests.
Changed
- Updated dependencies, including Nx
0.12.1and ExDoc0.40.3. - Reduced JIT recompilation warnings during training and hyperparameter tuning.
Documentation
- Updated release documentation for the transformer model.
0.1.2 - 2026-05-17
Changed
- Updated dependency versions.
- Fixed the Nx dependency version.
0.1.1 - 2026-04-19
Added
- Added model version 5 with a multi-scale architecture and made it the default at the time.
- Added tests for model version 5.
Changed
- Refactored model architecture names to be more descriptive.
- Updated CI to newer Elixir and OTP versions.
Fixed
- Fixed Axon deprecation warnings by using
Axon.ModelState.empty(). - Fixed compiler warnings and formatted tests.
0.1.0 - 2026-02-06
Added
- Added the initial binary text classification library built on Axon and Nx.
- Added tokenizer, vectorizer, training, serving, saving, and loading workflows.
- Added explicit label mapping support.
- Added configurable compiler/backend options for training and serving.
- Added model versioning for backward-compatible serialized classifiers.
- Added model versions 1 through 4, including CNN, mixed-pooling CNN, multi-scale CNN, and Sep-SE-CNN.
- Added hyperparameter auto-tuning for learning rate and dropout.
- Added
BinClass.compile_predictor/2for low-latency in-process inference. - Added examples for training, serving, configurable backends, and simple inference.
- Added Hex package metadata, MIT license, CI workflow, and Dependabot configuration.
Changed
- Optimized model architecture and training performance before the first tagged release.
- Reverted the experimental v5 work before
v0.1.0and kept v4 as the default at release time. - Marked the temporary-file helper module as internal.
Documentation
- Added and refined README, examples documentation, and module documentation for the initial Hex release.