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Reinforcement Learning for Relation Classification from Noisy Data(TensorFlow)

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作者您好: 对于您的代码,我完全按照流程,自己训练好模型,测试的联合模型结果为[0.52, 0.53, 0.44333333333333336],远低于您给的best_CNN_model的结果[0.8, 0.735,0.7066666666666667],同时原始CNN模型的效果也低于您文件中写的CNN模型效果。请问您在得到best模型使用了哪些效果提升的方法么? 不好意思打扰您了~

您好我在运行rlmodel.py的时候,一直选择的都是整个训练集的所有句子,并没有进行句子筛选,请问是怎么回事呢? chosen sentence size: 235962 total_reward: -1.0407107 best_reward -1.0406367 chosen sentence size: 235962 total_reward: -1.0407107 best_reward -1.0406367 chosen sentence size: 235962 total_reward: -1.0407109 best_reward -1.0406367 chosen sentence size: 235962 total_reward:...

在rlmodel 中定义sampletimes = 3 ,网络结构并没有改变,只是重复计算prob吗? list_state, list_action三次采样应该都是一样的值。 ``` for j in range(sampletimes): #reset environment state = env.reset( batch_en1, batch_en2,batch_sentence_ebd,batch_reward) list_action = [] list_state = [] old_prob = [] #get action...