fix change log#275
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This pull request updates the CHANGELOG.md file to document several new features and improvements for version 0.2.0, including Optimization.jl integration, per-branch optimizers, L2 regularization, improved YAML configuration saving, and enhanced data processing for MultiNNHybridModel. The feedback suggests a minor grammatical correction to ensure consistency in the changelog formatting.
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| - Per-Branch Optimizers: Enabled per-parameter/per-branch optimizer configurations using Optimisers.jl, allowing for more granular control over training dynamics. [#267](https://github.com/EarthyScience/EasyHybrid.jl/pull/267) | ||
| - Added L2 regularization support for model weights and introduced utility functions for weight extraction and norm calculation. [#267](https://github.com/EarthyScience/EasyHybrid.jl/pull/267) | ||
| - Improved YAML configuration saving to include parameter bounds and the full source code of mechanistic models for better reproducibility. [#267](https://github.com/EarthyScience/EasyHybrid.jl/pull/267) | ||
| - data processing for MultiNNHybridModel, including better sequence filtering and support for multi-branch neural network architectures. [#267](https://github.com/EarthyScience/EasyHybrid.jl/pull/267) |
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This bullet point starts with a lowercase letter and is grammatically incomplete compared to the other entries. It should start with a capitalized action verb like "Improved" to maintain consistency across the changelog.
| - data processing for MultiNNHybridModel, including better sequence filtering and support for multi-branch neural network architectures. [#267](https://github.com/EarthyScience/EasyHybrid.jl/pull/267) | |
| - Improved data processing for MultiNNHybridModel, including better sequence filtering and support for multi-branch neural network architectures. [#267](https://github.com/EarthyScience/EasyHybrid.jl/pull/267) |
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