From 07ab9ccaf885d753338e346c101dabfd98ac6c29 Mon Sep 17 00:00:00 2001 From: Piotr Czapla Date: Sun, 10 Feb 2019 09:53:42 +0100 Subject: [PATCH] Add first MLDoc results --- results/logs/de.md | 102 +++++++++++++++++++++++++++++++++++++++++++++ results/logs/fr.md | 20 +++++++++ 2 files changed, 122 insertions(+) create mode 100644 results/logs/de.md create mode 100644 results/logs/fr.md diff --git a/results/logs/de.md b/results/logs/de.md new file mode 100644 index 0000000..c486db3 --- /dev/null +++ b/results/logs/de.md @@ -0,0 +1,102 @@ += DE = +== VF60k LSTM nl 3 == +=== LM === +``` +python -m ulmfit lm --dataset-path data/wiki/de-100 --cuda-id=1 --tokenizer='vf' --nl 3 --name 'nl3' --max-vocab 60000 --lang de --qrnn=False - train 10 --bs=50 --drop_mult=0 +Max vocab: 60000 +Cache dir: data/wiki/de-100/models/vf60k +Model dir: data/wiki/de-100/models/vf60k/lstm_nl3.m +Running tokenization +Wiki text was split to 175965 articles +Wiki text was split to 110 articles +Size of vocabulary: 60003 +First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', ',', 'der', '.', 'und', 'die', 'in', "&'", 'von', 'den', '(', 'im', ')'] +Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': None, 'pretrained_model': None, 'drop_mult': 0} dps: [0.25 0.1 0.2 0.02 0.15] +Training lm from random weights +epoch train_loss valid_loss accuracy +1 3.214624 3.573368 0.397312 +2 3.194401 3.549021 0.396143 +3 3.116934 3.535322 0.398108 +4 3.159205 3.498862 0.400490 +5 3.104538 3.454015 0.405504 +6 2.996653 3.410940 0.409791 +7 2.987909 3.359425 0.413711 +8 2.941863 3.311215 0.419416 +9 2.914403 3.285807 0.423674 +10 2.857530 3.278313 0.425131 +data/wiki/de-100/models/vf60k +Saving info data/wiki/de-100/models/vf60k/lstm_nl3.m/info.json +``` +=== MLDocs === +... +== SP30k LSTM nl 4 == +=== LM === +``` +python -m ulmfit lm --dataset-path data/wiki/de-100 --cuda-id=0 --tokenizer='sp' --nl 4 --name 'nl4' --max-vocab 30000 --lang sp --qrnn=False - train 10 --bs=50 --drop_mult=0 +1,2.833101,3.174348,0.472863 +2,2.788717,3.171983,0.471377 +3,2.831292,3.187135,0.471068 +4,2.723390,3.133801,0.475572 +5,2.681617,3.064743,0.481984 +6,2.662792,2.984701,0.489080 +7,2.542035,2.892254,0.499275 +8,2.422225,2.806846,0.508663 +9,2.462655,2.736171,0.517994 +10,2.396778,2.714520,0.521145 +data/wiki/de-100/models/sp30k/lstm_nl4.m/lm-history.csv +``` + +=== MLDocs === +``` +python -m ulmfit cls --dataset-path data/mldoc/de-1 --base-lm-path data/wiki/de-100/models/sp30k/lstm_nl4.m --lang=de --name 'nl4' - train 20 --bs 40 ✘ 1 +Max vocab: 30000 +Cache dir: data/mldoc/de-1/models/sp30k +Model dir: data/mldoc/de-1/models/sp30k/lstm_nl4.m +Loading validation data/mldoc/de-1/de.dev.csv +Tokenized data loaded, lm.trn 13500, lm.val 1500 +Tokenized data loaded, cls.trn 1000, cls.val 1000 +Size of vocabulary: 30000 +First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '', '▁', '▁.', '▁,', '▁der', '▁die', '▁und', '▁in', 'en', "▁&'", 's', '-'] +Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('data/wiki/de-100/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('data/wiki/de-100/models/sp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15] +Unknown tokens 0, first 100: [] +Training lm from: [PosixPath('data/wiki/de-100/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('data/wiki/de-100/models/sp30k/lstm_nl4.m/../itos')] +epoch train_loss valid_loss accuracy +1 3.042075 2.457199 0.547201 +epoch train_loss valid_loss accuracy +1 2.581403 2.305440 0.565500 +2 2.366814 2.139165 0.589417 +3 2.187646 1.986698 0.612081 +4 2.054434 1.857322 0.630642 +5 1.948663 1.758499 0.644389 +6 1.850596 1.673632 0.655852 +7 1.813331 1.593225 0.668256 +8 1.738136 1.523946 0.678633 +9 1.683469 1.463405 0.688561 +10 1.609236 1.410462 0.697171 +11 1.599416 1.356008 0.706997 +12 1.526982 1.308399 0.715433 +13 1.487115 1.263120 0.723749 +14 1.430917 1.224060 0.731837 +15 1.410333 1.191501 0.738267 +16 1.385961 1.166404 0.743477 +17 1.349813 1.144801 0.747553 +18 1.345938 1.132679 0.750188 +19 1.311102 1.127321 0.751208 +20 1.355743 1.126064 0.751384 +Saving info data/mldoc/de-1/models/sp30k/lstm_nl4.m/info.json +Starting classifier training +epoch train_loss valid_loss accuracy +1 0.490199 0.246640 0.940000 +epoch train_loss valid_loss accuracy +1 0.302251 0.243051 0.932000 +epoch train_loss valid_loss accuracy +1 0.211028 0.249550 0.932000 +epoch train_loss valid_loss accuracy +1 0.159555 0.230822 0.947000 +2 0.144418 0.226450 0.943000 +Saving models at data/mldoc/de-1/models/sp30k/lstm_nl4.m +Loss and accuracy using (cls_last): [0.22645034, tensor(0.9430)] +Loss and accuracy using (cls_best): [0.22645034, tensor(0.9430)] +``` +MultiCCA: 93.7% , ulmfit: 94.3% + \ No newline at end of file diff --git a/results/logs/fr.md b/results/logs/fr.md new file mode 100644 index 0000000..757cd26 --- /dev/null +++ b/results/logs/fr.md @@ -0,0 +1,20 @@ += FR = +== VF60k LSTM nl 3 == +=== LM === +``` +``` +=== MLDocs === +``` +``` + +== SP30k LSTM nl 4 == +=== LM === +``` +python -m ulmfit lm --dataset-path data/wiki/fr-100 --cuda-id=1 --tokenizer='sp' --nl 4 --name 'nl4' --max-vocab 30000 \ +--lang fr --qrnn=False - train 10 --bs=50 --drop_mult=0 +``` + +=== MLDocs === +``` +``` +