“NLP Status Report 2017-6-5”版本间的差异

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第2行: 第2行:
 
!Date !! People !! Last Week !! This Week
 
!Date !! People !! Last Week !! This Week
 
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| rowspan="6"|2017/5/31
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| rowspan="6"|2017/6/5
 
|Jiyuan Zhang ||
 
|Jiyuan Zhang ||
 
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第13行: 第13行:
 
* big data baseline bleu = '''30.83'''
 
* big data baseline bleu = '''30.83'''
 
* Fixed three embeddings
 
* Fixed three embeddings
{| class="wikitable"
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  Shrink output vocab from 30000 to 20000 and best result is 31.53
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  Train the model with 40 batch size and best result until now is 30.63
! alpha
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! beta
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! result (bleu)
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|-
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| 1
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| 1
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| 43.50
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|-
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| 4/3
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| 2/3
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| 43.58 (w/o retrained)
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|-
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| 2/3
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| 4/3
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| 41.22 (w/o retrained)
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|-
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| 2/3
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| 4/3
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| 42.36 (w/ retrained)
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|}
 
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* experiments with '''constant''' initialized embedding:
+
* test more checkpoints on model trained with batch = 40
 
+
* train model with reverse output
 
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2017年6月5日 (一) 05:44的版本

Date People Last Week This Week
2017/6/5 Jiyuan Zhang
Aodong LI
  • Small data:
 Only make the English encoder's embedding constant -- 45.98
 Only initialize the English encoder's embedding and then finetune it -- 46.06
 Share the attention mechanism and then directly add them -- 46.20
  • big data baseline bleu = 30.83
  • Fixed three embeddings
 Shrink output vocab from 30000 to 20000 and best result is 31.53
 Train the model with 40 batch size and best result until now is 30.63
  • test more checkpoints on model trained with batch = 40
  • train model with reverse output

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|- |Shiyue Zhang ||

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|- |Shipan Ren ||

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