“Gigabye LM”版本间的差异
(→3. word-based 3-gram) |
(→3. word-based 3-gram) |
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第62行: | 第62行: | ||
|10k: - || 770M || 193M || 135M | |10k: - || 770M || 193M || 135M | ||
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− | |20k: - || - || | + | |20k: - || - || 217M || 142M |
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2012年9月13日 (四) 06:06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 | 2gram | 3gram | size | ppl | fst size |
---|---|---|---|---|---|
1 | 1e-7 | 1e-7 | 30M | ppl= 102.796 | 860M |
2 | 1e-6 | 1e-6 | 5M | ppl= 150.96 | 152M |
3 | 1e-7 | 1e-6 | 11M | ppl= 137.467 | 224M |
3. word-based 3-gram
tri-gram size:
org | th-7 | th-7/6 | th-6 |
10k: 52M | 23M | 8M | 4M |
20k: 57M | 24M | 9M | 4M |
final fst size:
org | th-7 | th-7/6 | th-6 |
10k: - | 770M | 193M | 135M |
20k: - | - | 217M | 142M |