indicators that require the assistance of algorithm
Posted: Mon Dec 23, 2024 6:43 am
It is difficult to reach a consensus, which affects the team's accurate understanding and decision-making of model performance. A detailed set of evaluation guidelines needs to be formulated, including evaluation indicator scoring standards and operating procedures. . Basic process of evaluation The general steps and processes of model evaluation include the following key stages. Collecting necessary information requires collecting data documents required for model evaluation. This time, our company wants to verify the feasibility of the knowledge base in low-code products, so the data used is the standard training manual of the product.Usually the training data set requires the following data with different uses, but it can be selected according to the needs of the enterprise.
The training data set is used for the initial iran phone number format learning process of the model. The validation data set is used for model parameter adjustment and hyperparameter optimization. The test data set is used to evaluate the final performance of the model. Labeled data If the model needs to perform supervised learning, labeled data is required. . Detailed explanation of evaluation indicators After confirming the purpose of the enterprise evaluation in the model evaluation, you first need to confirm the required evaluation indicators. Only with indicators can you better determine the questions asked by the model.
The following indicators are used to measure different aspects of the model to help developers and decision makers understand the performance of the model in actual applications. What kind of person is suitable to be an end product manager? To become an excellent end product manager, understanding the business and understanding the product are two very important criteria.The end track is very segmented, and the speed of product iteration and promotion is also very slow, which creates a large number of job opportunities. View details> Basic capabilities of large models Multi-round dialogue understanding evaluates whether the model can understand and remember the contextual information in multiple rounds of dialogue.
The training data set is used for the initial iran phone number format learning process of the model. The validation data set is used for model parameter adjustment and hyperparameter optimization. The test data set is used to evaluate the final performance of the model. Labeled data If the model needs to perform supervised learning, labeled data is required. . Detailed explanation of evaluation indicators After confirming the purpose of the enterprise evaluation in the model evaluation, you first need to confirm the required evaluation indicators. Only with indicators can you better determine the questions asked by the model.
The following indicators are used to measure different aspects of the model to help developers and decision makers understand the performance of the model in actual applications. What kind of person is suitable to be an end product manager? To become an excellent end product manager, understanding the business and understanding the product are two very important criteria.The end track is very segmented, and the speed of product iteration and promotion is also very slow, which creates a large number of job opportunities. View details> Basic capabilities of large models Multi-round dialogue understanding evaluates whether the model can understand and remember the contextual information in multiple rounds of dialogue.