- Run any notebook using Jupyter Notebook.
Based on 20 epochs accuracy. The results will be different on different dataset. Trained on a GTX 960, 4GB VRAM.
name | accuracy |
---|---|
1.basic-seq2seq-manual | 0.915255 |
2.lstm-seq2seq-manual | 0.917009 |
3.gru-seq2seq-manual | 0.920200 |
4.basic-seq2seq-api-greedy | 0.960998 |
5.lstm-seq2seq-api-greedy | 0.202590 |
6.gru-seq2seq-greedy | 0.408099 |
7.basic-birnn-seq2seq-manual | 0.919491 |
8.lstm-birnn-seq2seq-manual | 0.918473 |
9.gru-birnn-seq2seq-manual | 0.922818 |
10.basic-birnn-seq2seq-greedy | 0.957355 |
11.lstm-birnn-seq2seq-greedy | 0.202628 |
12.gru-birnn-seq2seq-greedy | 0.484461 |
13.basic-seq2seq-luong | 0.916100 |
14.lstm-seq2seq-luong | 0.917736 |
15.gru-seq2seq-luong | 0.919482 |
16.basic-seq2seq-bahdanau | 0.915700 |
17.lstm-seq2seq-bahdanau | 0.721833 |
18.gru-seq2seq-bahdanau | 0.919218 |
19.lstm-birnn-seq2seq-luong | 0.918555 |
20.gru-birnn-seq2seq-luong | 0.919445 |
21.lstm-birnn-seq2seq-bahdanau | 0.917655 |
22.gru-birnn-seq2seq-bahdanau | 0.920555 |
23.lstm-birnn-seq2seq-bahdanau-luong | 0.918182 |
24.gru-birnn-seq2seq-bahdanau-luong | 0.920045 |
25.lstm-seq2seq-greedy-luong | 0.364322 |
26.gru-seq2seq-greedy-luong | 0.627814 |
27.lstm-seq2seq-greedy-bahdanau | 0.378199 |
28.gru-seq2seq-greedy-bahdanau | 0.470696 |
29.lstm-seq2seq-beam | 0.122135 |
30.gru-seq2seq-beam | 0.163046 |
31.lstm-birnn-seq2seq-beam-luong | 0.171741 |
32.gru-birnn-seq2seq-beam-luong | 0.189787 |
33.lstm-birnn-seq2seq-luong-bahdanau-stack-beam | 0.098961 |
34.gru-birnn-seq2seq-luong-bahdanau-stack-beam | 0.091473 |
35.byte-net | 1.022409 |
36.estimator | |
37.capsule-lstm-seq2seq-greedy | |
38.capsule-lstm-seq2seq-luong-beam | |
39.lstm-birnn-seq2seq-luong-bahdanau-stack-beam-dropout-l2 | 0.066305 |
40.dnc-seq2seq-bahdanau-greedy | 0.711184 |
41.lstm-birnn-seq2seq-beam-luongmonotic | 0.624756 |
42.lstm-birnn-seq2seq-beam-bahdanaumonotic | 0.624756 |
43.memory-network-basic | 0.965700 |
44.memory-network-lstm | 0.942591 |
45.attention-is-all-you-need | 0.170279 |
46.transformer-xl | 0.114907 |
47.attention-is-all-you-need-beam-search | 0.158205 |
48.conv-encoder-conv-decoder | 0.462655 |
49.conv-encoder-lstm | 0.438702 |
50.byte-net-greedy.ipynb | 1.023528 |
51.gru-birnn-seq2seq-greedy-residual.ipynb | 0.561457 |
52.google-nmt.ipynb | 0.675990 |
53.dilated-seq2seq.ipynb | 1.023615 |