训练AI模型就像是炼丹…😄
#AI模型训练 #炼丹
看公司小伙伴训练AI模型，通过优化输入层例如拉宽数值时间区间和增加典型特征值，调整隐藏层层级和改变部分层的类型，模型的验证精度提升了30多个百分点。
#炼丹⚗️持续中~
公司小伙伴报告，服务器端AI模型经过低位整型化处理后，运行效率提升数十倍，推理精度仅降低约3%，发布到较低算力边缘设备上测试运行良好，基本达到预期目标。🧙🔮
Training an AI model is just like refining alchemy…😄
#AIModelTraining #Alchemy
Train AI models by optimizing the input layer, such as widening the TSD time range and adding typical feature values, adjusting the hierarchy of hidden layers, and changing the types of some layers, the validation accuracy of the model increased by more than 30 percentage points.
#Alchemy⚗️Continues~
After processing the server-side AI model with low-bit integer quantization, the running efficiency improved by dozens of times, with inference accuracy reduced by only about 3%. When deployed to edge devices with low computing power, it performed well, basically achieving the expected goals.🧙🔮
