Fig. 7: Modeling fine-tuning strategy and results for various sized datasets. | Nature Communications

Fig. 7: Modeling fine-tuning strategy and results for various sized datasets.

From: Scale-up of complex molecular reaction system by hybrid mechanistic modeling and deep transfer learning

Fig. 7

a Modeling fine-tuning strategy. The data used for fine-tuning the model was generated from 15 sets of pilot-scale data using interpolation. The generated data was randomly divided into training and validation sets with an 8:2 ratio. After fine-tuning the model, experimental data were used as a testing set to validate the results. b Mean absolute error (MAE) of training, validation, and testing sets for various sized datasets. c Mean square error (MSE) of training, validation, and testing sets for various sized datasets. A dataset size of 60 samples was selected as the optimal dataset for this work. Source data are provided as a Source data file.

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