lonepatient/cw2vec-pytorch

cw2vec implementation in pytorch

cw2vec-pytorch's Issues

实验结果问题

您好，请问您的实现结果是否与论文结果一致？

咨询，麻烦帮忙解答一下

你好，请问这样是已经在训练了吗
[training] 542615/15000050 [ ] -0.1s/step loss: 1.[training] 542616/15000050 [ ] -0.1s/step loss: 0.[training] 542617/15000050 [ ] -0.1s/step loss: 0.[training] 542618/15000050 [ ] -0.1s/step loss: 1.[training] 542619/15000050 [ ] -0.1s/step loss: 1.[training] 542620/15000050 [ ] -0.1s/step loss: 1.[training] 542621/15000050 [ ] -0.1s/step loss: 1.[training] 542622/15000050 [ ] -0.1s/step loss: 1.[training] 542623/15000050 [ ] -0.1s/step loss: 0.[training] 542624/15000050 [ ] -0.1s/step loss: 0.[training] 542625/15000050 [ ] -0.1s/step loss: 0.[training] 542626/15000050 [ ] -0.1s/step loss: 0.[training] 542627/15000050 [ ] -0.1s/step loss: 0.[training] 542628/15000050 [ ] -0.1s/step loss: 0.[training] 542629/15000050 [ ] -0.1s/step loss: 0.[training] 542630/15000050 [ ] -0.1s/step loss: 0.[training] 542631/15000050 [ ] -0.1s/step loss: 0.[training] 542632/15000050 [ ] -0.1s/step loss: 0.[training] 542633/15000050 [ ] -0.1s/step loss: 0.[training] 542634/15000050 [ ] -0.1s/step loss: 1.[training] 542635/15000050 [ ] -0.1s/step loss: 1.[training] 542636/15000050 [ ] -0.1s/step loss: 0.[training] 542637/15000050 [ ] -0.1s/step loss: 0.[training] 542638/15000050 [ ] -0.1s/step loss: 1.[training] 542639/15000050 [ ] -0.1s/step loss: 1.[training] 542640/15000050 [ ] -0.1s/step loss: 2.[training] 542641/15000050 [ ] -0.1s/step loss: 2.[training] 542642/15000050 [ ] -0.1s/step loss: 1.[training] 542643/15000050 [ ] -0.1s/step loss: 2.[training] 542644/15000050 [ ] -0.1s/step loss: 3.[training] 542645/15000050 [ ] -0.1s/step loss: 1.[training] 542646/15000050 [ ] -0.1s/step loss: 1.[training] 542647/15000050 [ ] -0.1s/step loss: 2.[training] 542648/15000050 [ ] -0.1s/step loss: 1.[training] 542649/15000050 [ ] -0.1s/step loss: 3.[training] 542650/15000050 [ ] -0.1s/step loss: 1.[training] 542651/15000050 [ ] -0.1s/step loss: 1.[training] 542652/15000050 [ ] -0.1s/step loss: 1.[training] 542653/15000050 [ ] -0.1s/step loss: 0.[training] 542654/15000050 [ ] -0.1s/step loss: 3.[training] 542655/15000050 [ ] -0.1s/step loss: 3.[training] 542656/15000050 [ ] -0.1s/step loss: 4.[training] 542657/15000050 [ ] -0.1s/step loss: 1.[training] 542658/15000050 [ ] -0.1s/step loss: 2.[training] 542659/15000050 [ ] -0.1s/step loss: 3.[training] 542660/15000050 [ ] -0.1s/step loss: 4.[training] 542661/15000050 [ ] -0.1s/step loss: 1.[training] 542662/15000050 [ ] -0.1s/step loss

训练数据问题

训练出错

使用提供的raw数据和自己做的分词数据进行训练都遇到了这样的问题, 请问这个keyError的原因可能是什么?

[training] 136536/498250 [>>>>>>>> ] -0.0s/step loss: 1.4116 [2019-07-08 23:25:35]: cw2vec trainer.py[line:79] INFO saving word2vec vector
save vector: 67%|██████▋ | 8839/13259 [00:00<00:00, 17438.27it/s]
Traceback (most recent call last):
File "E:/workstation/cw2vec-pytorch/train_cw2vec.py", line 95, in
main()
File "E:/workstation/cw2vec-pytorch/train_cw2vec.py", line 76, in main
trainer.train()
File "E:\workstation\cw2vec-pytorch\pycw2vec\train\trainer.py", line 145, in train
self.save()
File "E:\workstation\cw2vec-pytorch\pycw2vec\train\trainer.py", line 87, in save
word = id_word[i]
KeyError: 9965

损失函数一直不收敛

请问损失函数一直不收敛，这是什么原因

数据集问题

我想问下，zhihu.txt是已经分词过后的数据吗?

运行train_cw2vec时报错

RuntimeError: CUDA error: invalid device ordinal
报错如上，因为想进行word_similarity的任务，所以需要得到词和词向量一一对应的文件，所以要运行train_cw2vec，但是现在运行报错，服务器是拥有GPU的，希望能有人解答一下