Date |
Person |
start |
leave |
hours |
status
|
2017/04/02
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/03
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/04
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/05
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/06
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/07
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/08
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/09
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/10
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/11
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/12
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/13
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/14
|
Andy Zhang |
9:30 |
18:30 |
8 |
|
Peilun Xiao |
|
|
|
|
2017/04/15
|
Andy Zhang |
9:00 |
15:00 |
6 |
|
Peilun Xiao |
|
|
|
|
2017/04/18
|
Aodong Li |
11:00 |
20:00 |
8 |
- Pick up new task in news generation and do literature review
|
2017/04/19
|
Aodong Li |
11:00 |
20:00 |
8 |
|
2017/04/20
|
Aodong Li |
12:00 |
20:00 |
8 |
|
2017/04/21
|
Aodong Li |
12:00 |
20:00 |
8 |
|
2017/04/24
|
Aodong Li |
11:00 |
20:00 |
8 |
- Adjust literature review focus
|
2017/04/25
|
Aodong Li |
11:00 |
20:00 |
8 |
|
2017/04/26
|
Aodong Li |
11:00 |
20:00 |
8 |
|
2017/04/27
|
Aodong Li |
11:00 |
20:00 |
8 |
- Try to reproduce sc-lstm work
|
2017/04/28
|
Aodong Li |
11:00 |
20:00 |
8 |
- Transfer to new task in machine translation and do literature review
|
2017/04/30
|
Aodong Li |
11:00 |
20:00 |
8 |
|
2017/05/01
|
Aodong Li |
11:00 |
20:00 |
8 |
|
2017/05/02
|
Aodong Li |
11:00 |
20:00 |
8 |
- Literature review and code review
|
2017/05/06
|
Aodong Li |
14:20 |
17:20 |
3 |
|
2017/05/07
|
Aodong Li |
13:30 |
22:00 |
8 |
- Code review and experiment started, but version discrepancy encountered
|
2017/05/08
|
Aodong Li |
11:30 |
21:00 |
8 |
- Code review and version discrepancy solved
|
2017/05/09
|
Aodong Li |
13:00 |
22:00 |
9 |
- Code review and experiment
- details about experiment:
small data,
1st and 2nd translator uses the same training data,
2nd translator uses random initialized embedding
BASELINE: 43.87
best result of our model: 42.56
|
2017/05/10
|
Shipan Ren |
9:00 |
20:00 |
11 |
- Entry procedures
- Machine Translation paper reading
|
Aodong Li |
13:30 |
22:00 |
8 |
small data,
1st and 2nd translator uses the different training data, counting 22000 and 22017 seperately
2nd translator uses random initialized embedding
BASELINE: 36.67 (36.67 is the model at 4750 updates, but we use model at 3000 updates to prevent the case of overfitting, to generate the 2nd translator's training data, for which the BLEU is 34.96)
best result of our model: 29.81
- This may suggest that that using either the same training data with 1st translator or different one won't influence 2nd translator's performance, instead, using the same one may be better, at least from results. But I have to give a consideration of a smaller size of training data compared to yesterday's model.
- code 2nd translator with constant embedding
|
2017/05/11
|
Shipan Ren |
10:00 |
19:30 |
9.5 |
- Configure environment
- Run tf_translate code
- Read Machine Translation paper
|
Aodong Li |
13:00 |
|
|
|