实现基于深度学习的文本分类任务，采用sst2数据集，网络模型采用基本的lstm和rnn模型，并再次基础上引入bert的预训练embedding层以及attention来进行优化。本次文本分类任务完整的流程包括：库导入、数据集处理与加载、网络模型的构建、损失函数和优化器、训练和验证主循环构建、损失和准确率曲线、网络模型的加载与保存以及最后的模型测试。
active 2024-03-20 → 2024-03-20 (UTC)
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