“Gigabye LM”版本间的差异
（→3. word-based 3-gram） |
（→3. word-based 3-gram） |
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{| class="wikitable" | {| class="wikitable" | ||
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| − | | org || th-7 || th-6.5 || th-6 | + | | org || th-7 || th-6.5 || th-6 |
|- | |- | ||
| − | |10k: 52M || 23M || 8M || 4M | + | |10k: 52M || 23M || 8M || 4M |
|- | |- | ||
| − | |20k: 57M || 24M || 9M || 4M | + | |20k: 57M || 24M || 9M || 4M |
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| − | } | + | |} |
2012年9月13日 (四) 05:11的版本
1. very initial, without any prunning, character based. Here is the size and perplexity.
The training is with Gigabytes except the cna data, and ppl testing is based on a sub set from the cna data (big52gb applied)
2gram:
25M 2gram.4000.gz: 0 zeroprobs, logprob= -9.39983e+06 ppl= 161.965 ppl1= 177.141
3gram:
47M 3gram.500.gz:0 zeroprobs, logprob= -6.34868e+06 ppl= 85.1361 ppl1= 94.2525
117M 3gram.1000.gz :0 zeroprobs, logprob= -7.43809e+06 ppl= 80.6408 ppl1= 87.7439
195M 3gram.2000.gz:0 zeroprobs, logprob= -7.95872e+06 ppl= 79.9875 ppl1= 86.5196
221M 3gram.3000.gz:0 zeroprobs, logprob= -8.04799e+06 ppl= 80.2418 ppl1= 86.7277
229M 3gram.4000.gz:0 zeroprobs, logprob= -8.15697e+06 ppl= 82.6585 ppl1= 89.3392
4gram:
205M 4gram.500.gz:0 zeroprobs, logprob= -6.25395e+06 ppl= 79.6739 ppl1= 88.0716
472M 4gram.1000.gz:0 zeroprobs, logprob= -7.21607e+06 ppl= 70.737 ppl1= 76.774
2. pruning the 4k 3gram LM.
Model 1gram 2gram 3gram size ppl 1 1e-7 1e-7 1e-7 30M logprob= -8.55982e+06 ppl= 102.796 ppl1= 111.532 2 1e-6 1e-6 1e-6 5M logprob= -9.26982e+06 ppl= 150.96 ppl1= 164.9 3 1e-7 1e-6.5 1e-6.5 11M logprob= -9.09681e+06 ppl= 137.467 ppl1= 149.913
3. word-based 3-gram
| org | th-7 | th-6.5 | th-6 |
| 10k: 52M | 23M | 8M | 4M |
| 20k: 57M | 24M | 9M | 4M |
