Natural Language Processing Practical Project 16- Full-process guidance, model tuning and evaluation of actual combat training of large language models based on CPU

Hello everyone, I am Weixue AI. Today I will introduce to you Natural Language Processing Practical Project 16-CPU-based Generative Large Language Model Practical Training Full Process Detailed Explanation, Model Tuning and Evaluation. The process covers steps such as data preparation, data preprocessing, vocabulary construction, model selection and configuration, model training, model tuning, and model evaluation. Through continuous iteration and optimization, the performance of the model and the quality of the generated text can be improved.

Contents
1. Construction of generative large language model
2. Data loading model design
3. Model training function
4. Training classes and parameter settings
5. Start training
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1. Generative large language model construction

The backbone architecture of the model in this paper is the T5 model, which uses the Transformer structure and performs task migration through pre-training and fine-tuning.

The T5 model includes the encoder Encoder and the decoder Decoder. Transformer uses the self-attention mechanism (Self-Attention) to realize the modeling of the input sequence. For an input sequence ( X = x 1 , x 2

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Origin blog.csdn.net/weixin_42878111/article/details/132544716