mirror of
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485 lines
26 KiB
Markdown
485 lines
26 KiB
Markdown
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### MLDoc laser zero shoot 10k
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data/mldoc/de-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.9052500128746033
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data/mldoc/es-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.6974999904632568
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data/mldoc/fr-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.8740000128746033
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data/mldoc/it-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.7272499799728394
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data/mldoc/zh-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.8144999742507935
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```
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python -m ulmfit eval --glob="mldoc/*-1/models/sp15k/qrnn_nl4.m" --dataset_template='${lang}-10-laser-en1' --name rnd_nl4 --num-cls-epochs=8 --label-smoothing-eps=0.1 --lr_sched=1cycle --bs=18 --random-init=True
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python -m ulmfit eval --glob="mldoc/*-1/models/sp15k/qrnn_nl4.m" --dataset_template='${lang}-10-laser-en1' --name rnd_nl4 --num-cls-epochs=8 --label-smoothing-eps=0.1 --lr_sched=1cycle --bs=18 --random-init=True
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Processing data/mldoc/de-1/models/sp15k/qrnn_nl4.m
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de-10-laser-en1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-10-laser-en1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-10-laser-en1/de.dev.csv
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Data lm, trn: 13500, val: 1500
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Data cls, trn: 10000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁.', '▁,', '▁der', '▁die', 'en', '▁und', 's', '▁in', 'er', "▁&'"]
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/home/pczapla/anaconda3/envs/fastaiv1/lib/python3.7/site-packages/torch/utils/cpp_extension.py:152: UserWarning:
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!! WARNING !!
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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Your compiler (c++) may be ABI-incompatible with PyTorch!
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Please use a compiler that is ABI-compatible with GCC 4.9 and above.
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See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
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See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
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for instructions on how to install GCC 4.9 or higher.
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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!! WARNING !!
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warnings.warn(ABI_INCOMPATIBILITY_WARNING.format(compiler))
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Starting classifier from random weights
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 0.864752 0.760891 0.844000
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2 0.734504 1.077554 0.676000
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3 0.681645 0.703327 0.885000
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4 0.670696 0.779010 0.898000
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5 0.620256 0.664871 0.910000
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6 0.591837 1.077103 0.915000
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7 0.550238 0.607863 0.913000
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8 0.543874 0.607274 0.918000
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Total time: 19:55
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Loss and accuracy using (cls_best): [0.35624045, tensor(0.9053)]
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Processing data/mldoc/en-1/models/sp15k/qrnn_nl4.m
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en-10-laser-en1
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Processing data/mldoc/es-1/models/sp15k/qrnn_nl4.m
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es-10-laser-en1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-10-laser-en1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-10-laser-en1/es.dev.csv
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Data lm, trn: 13013, val: 1445
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Data cls, trn: 9458, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', 's', '▁en', '▁el', '▁y', '▁a', '▁que']
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Starting classifier from random weights
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 0.755512 1.360725 0.500000
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2 0.760655 1.362604 0.399000
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3 0.760876 20.748863 0.607000
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4 0.730208 8.120344 0.369000
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5 0.707735 1.149775 0.700000
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6 0.679102 1.010318 0.746000
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7 0.639611 3.087066 0.713000
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8 0.608591 1.327793 0.750000
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Total time: 11:38
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Loss and accuracy using (cls_best): [1.3680531, tensor(0.6975)]
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Processing data/mldoc/fr-1/models/sp15k/qrnn_nl4.m
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fr-10-laser-en1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-10-laser-en1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-10-laser-en1/fr.dev.csv
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Data lm, trn: 13500, val: 1500
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Data cls, trn: 10000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', 's', '▁.', "'", '▁la', '▁le', '▁et', '▁l', '▁à']
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Starting classifier from random weights
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 0.922996 1.406875 0.519000
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2 0.833284 1.172545 0.640000
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3 0.749922 0.697733 0.863000
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4 0.724680 0.735842 0.837000
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5 0.652541 0.679455 0.876000
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6 0.641541 0.671731 0.868000
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7 0.577571 0.734958 0.868000
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8 0.579186 0.703696 0.883000
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Total time: 19:15
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Loss and accuracy using (cls_best): [0.47713563, tensor(0.8740)]
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Processing data/mldoc/it-1/models/sp15k/qrnn_nl4.m
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it-10-laser-en1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-10-laser-en1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-10-laser-en1/it.dev.csv
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Data lm, trn: 13500, val: 1500
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Data cls, trn: 10000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁di', '▁e', "▁&'", "'", '▁il', '▁la', '▁in', 'e']
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Starting classifier from random weights
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 0.991065 1.602189 0.381000
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2 0.935880 0.888808 0.734000
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3 0.860670 0.868564 0.781000
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4 0.818734 0.945302 0.791000
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5 0.751467 3.113552 0.808000
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6 0.687606 0.921033 0.795000
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7 0.677044 1.222023 0.807000
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8 0.645511 1.418593 0.805000
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Total time: 11:44
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Loss and accuracy using (cls_best): [1.1276722, tensor(0.7272)]
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Processing data/mldoc/ja-1/models/sp15k/qrnn_nl4.m
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ja-10-laser-en1
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Processing data/mldoc/zh-1/models/sp15k/qrnn_nl4.m
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zh-10-laser-en1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-10-laser-en1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-10-laser-en1/zh.dev.csv
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Data lm, trn: 13500, val: 1500
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Data cls, trn: 10000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁的', '▁。', '▁年', '▁、', '▁在', '▁一', '▁是', '▁中', '▁有']
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Starting classifier from random weights
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 0.920411 1.159853 0.629000
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2 0.937020 1.371089 0.527000
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3 0.892036 3.091183 0.615000
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4 0.839919 0.939323 0.724000
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5 0.797184 1.174206 0.735000
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6 0.774195 0.914951 0.733000
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7 0.744524 0.875888 0.762000
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8 0.721782 0.825969 0.788000
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Total time: 19:53
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m
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Loss and accuracy using (cls_best): [0.54084456, tensor(0.8145)]
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OrderedDict([('data/mldoc/de-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m',
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0.9052500128746033),
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('data/mldoc/es-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m',
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0.6974999904632568),
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('data/mldoc/fr-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m',
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0.8740000128746033),
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('data/mldoc/it-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m',
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0.7272499799728394),
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('data/mldoc/zh-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m',
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0.8144999742507935)])
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data/mldoc/de-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.9052500128746033
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data/mldoc/es-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.6974999904632568
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data/mldoc/fr-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.8740000128746033
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data/mldoc/it-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.7272499799728394
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data/mldoc/zh-10-laser-en1/models/sp15k/qrnn_rnd_nl4.m: 0.8144999742507935
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```
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### MLDoc Classification on 1k
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data/mldoc/de-1/models/sp15k/qrnn_rnd-nl4.m: 0.9024999737739563
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data/mldoc/en-1/models/sp15k/qrnn_rnd-nl4.m: 0.8149999976158142
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data/mldoc/es-1/models/sp15k/qrnn_rnd-nl4.m: 0.8964999914169312
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data/mldoc/fr-1/models/sp15k/qrnn_rnd-nl4.m: 0.8220000267028809
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data/mldoc/it-1/models/sp15k/qrnn_rnd-nl4.m: 0.7889999747276306
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data/mldoc/ja-1/models/sp15k/qrnn_rnd-nl4.m: 0.8302500247955322
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data/mldoc/ru-1/models/sp15k/qrnn_rnd-nl4.m: 0.7319999933242798
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data/mldoc/zh-1/models/sp15k/qrnn_rnd-nl4.m: 0.8452500104904175
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```
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python -m ulmfit eval --glob="wiki/*-100/models/sp15k/qrnn_rnd-nl4.m" --name rnd-nl4 --dataset-template='../mldoc/${lang}-1' --num-lm-epochs=0 --num-cls-epochs=8 --bs=18 --lr_sched=1cycle --label-smoothing-eps=0.1
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Processing data/wiki/de-100/models/sp15k/qrnn_rnd-nl4.m
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../mldoc/de-1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp15k/qrnn_rnd-nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/de.dev.csv
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Data lm, trn: 13500, val: 1500
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Data cls, trn: 1000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁.', '▁,', '▁der', '▁die', 'en', '▁und', 's', '▁in', 'er', "▁&'"]
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Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
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/home/pczapla/anaconda3/envs/fastaiv1/lib/python3.7/site-packages/torch/utils/cpp_extension.py:152: UserWarning:
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!! WARNING !!
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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Your compiler (c++) may be ABI-incompatible with PyTorch!
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Please use a compiler that is ABI-compatible with GCC 4.9 and above.
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See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
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See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
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for instructions on how to install GCC 4.9 or higher.
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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!! WARNING !!
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warnings.warn(ABI_INCOMPATIBILITY_WARNING.format(compiler))
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Loading pretrained model
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Unknown tokens 0, first 100: []
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Bptt 70
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/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp15k
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Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp15k/qrnn_rnd-nl4.m/info.json
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 1.411651 1.386593 0.265000
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2 1.287022 1.488027 0.361000
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3 1.084153 2.390431 0.370000
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4 0.904227 0.936213 0.769000
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5 0.740495 1.311880 0.538000
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6 0.642756 0.754690 0.833000
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7 0.582816 0.661088 0.892000
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8 0.548893 0.683635 0.875000
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Total time: 02:13
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp15k/qrnn_rnd-nl4.m
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Loss and accuracy using (cls_best): [0.33525154, tensor(0.9025)]
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Processing data/wiki/en-100/models/sp15k/qrnn_rnd-nl4.m
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../mldoc/en-1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/en-1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/en-1/models/sp15k/qrnn_rnd-nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/en-1/en.dev.csv
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Data lm, trn: 13500, val: 1500
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Data cls, trn: 1000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
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First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁the', '▁,', 's', '▁.', '▁of', '▁and', '▁in', '▁to', '▁a', 'ed']
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Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
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Loading pretrained model
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Unknown tokens 0, first 100: []
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Bptt 70
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/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/en-1/models/sp15k
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Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/en-1/models/sp15k/qrnn_rnd-nl4.m/info.json
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Single training schedule
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epoch train_loss valid_loss accuracy
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1 1.369466 1.356636 0.374000
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2 1.263357 2.515120 0.320000
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3 1.119744 1.250081 0.569000
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4 0.949653 1.033515 0.666000
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5 0.802069 0.875799 0.779000
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6 0.676997 0.842525 0.807000
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7 0.613777 0.794573 0.826000
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8 0.571342 0.781615 0.837000
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Total time: 02:26
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Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/en-1/models/sp15k/qrnn_rnd-nl4.m
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Loss and accuracy using (cls_best): [0.5295334, tensor(0.8150)]
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Processing data/wiki/es-100/models/sp15k/qrnn_rnd-nl4.m
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../mldoc/es-1
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Max vocab: 15000
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Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k
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Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_rnd-nl4.m
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Training
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Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
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Data lm, trn: 13013, val: 1445
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Data cls, trn: 1000, val: 1000
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Data tst, trn: 1000, val: 4000
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Size of vocabulary: 15000
|
||
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', 's', '▁en', '▁el', '▁y', '▁a', '▁que']
|
||
Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
|
||
Loading pretrained model
|
||
Unknown tokens 2621, first 100: ['▁sa', '▁i', 'ncia', '▁ka', '▁k', '▁tra', '▁fi', '▁volvi', '▁g', '▁man', '▁pasó', '▁tropas', 'pon', 'tuvieron', '▁x', '▁les', '▁empez', 'ieron', '▁bas', 'sco', '▁cam', '▁adapta', 'sion', '▁mol', 'pico', 'siones', '▁obstante', '▁!', '▁w', 'cular', 'puesta', '▁inten', '▁produj', 'clu', 'simismo', '▁pas', 'fla', '▁amerindio', 'aje', '▁deja', '▁fre', '▁jo', '▁2.', 'american', '▁cre', 'bajo', '▁medi', 'gla', '▁dirigi', 'hol', '▁aparición', 'aciones', 'vivi', 'eras', 'spe', '▁continu', '▁permaneci', '▁ber', 'usa', 'bió', '▁permitió', '▁municipios', '▁regres', 'rt', 'mbi', '▁pr', '▁ofreci', 'emi', 'misiones', '▁cap', '▁ram', 'icio', '▁wal', 'fru', '▁gen', '▁originalmente', '▁eva', '▁ferr', '▁descubri', '▁aparecen', '▁fon', 'capi', 'estre', 'pec', '▁vendi', 'iéndose', 'eja', 'liber', 'nsa', 'ológico', 'ío', 'blo', '▁tro', '▁aviones', 'cara', '▁activo', 'mostró', 'disciplina', '▁ara', 'estra']
|
||
Bptt 70
|
||
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k
|
||
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_rnd-nl4.m/info.json
|
||
Single training schedule
|
||
epoch train_loss valid_loss accuracy
|
||
1 1.378275 1.354129 0.314000
|
||
2 1.209560 1.333649 0.507000
|
||
3 1.022200 0.820093 0.801000
|
||
4 0.854187 1.782254 0.389000
|
||
5 0.722861 1.031932 0.692000
|
||
6 0.640640 0.762994 0.853000
|
||
7 0.583225 0.677089 0.901000
|
||
8 0.556481 0.652575 0.904000
|
||
Total time: 01:59
|
||
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Loss and accuracy using (cls_best): [0.35487488, tensor(0.8965)]
|
||
Processing data/wiki/fr-100/models/sp15k/qrnn_rnd-nl4.m
|
||
../mldoc/fr-1
|
||
Max vocab: 15000
|
||
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp15k
|
||
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Training
|
||
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/fr.dev.csv
|
||
Data lm, trn: 13500, val: 1500
|
||
Data cls, trn: 1000, val: 1000
|
||
Data tst, trn: 1000, val: 4000
|
||
Size of vocabulary: 15000
|
||
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', 's', '▁.', "'", '▁la', '▁le', '▁et', '▁l', '▁à']
|
||
Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
|
||
Loading pretrained model
|
||
Unknown tokens 0, first 100: []
|
||
Bptt 70
|
||
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp15k
|
||
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp15k/qrnn_rnd-nl4.m/info.json
|
||
Single training schedule
|
||
epoch train_loss valid_loss accuracy
|
||
1 1.360408 1.298057 0.444000
|
||
2 1.251207 2.454086 0.393000
|
||
3 1.098488 1.152682 0.544000
|
||
4 0.926239 1.256870 0.622000
|
||
5 0.806994 0.911339 0.732000
|
||
6 0.717139 0.945148 0.726000
|
||
7 0.635195 0.781772 0.825000
|
||
8 0.602214 0.763521 0.825000
|
||
Total time: 02:17
|
||
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Loss and accuracy using (cls_best): [0.52210134, tensor(0.8220)]
|
||
Processing data/wiki/it-100/models/sp15k/qrnn_rnd-nl4.m
|
||
../mldoc/it-1
|
||
Max vocab: 15000
|
||
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp15k
|
||
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Training
|
||
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/it.dev.csv
|
||
Data lm, trn: 13500, val: 1500
|
||
Data cls, trn: 1000, val: 1000
|
||
Data tst, trn: 1000, val: 4000
|
||
Size of vocabulary: 15000
|
||
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁di', '▁e', "▁&'", "'", '▁il', '▁la', '▁in', 'e']
|
||
Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
|
||
Loading pretrained model
|
||
Unknown tokens 0, first 100: []
|
||
Bptt 70
|
||
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp15k
|
||
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp15k/qrnn_rnd-nl4.m/info.json
|
||
Single training schedule
|
||
epoch train_loss valid_loss accuracy
|
||
1 1.357973 1.353393 0.293000
|
||
2 1.282061 1.535401 0.390000
|
||
3 1.144333 1.480346 0.533000
|
||
4 0.985930 1.360542 0.540000
|
||
5 0.862014 1.285450 0.661000
|
||
6 0.720891 1.140574 0.629000
|
||
7 0.625376 0.840085 0.791000
|
||
8 0.572435 0.828283 0.793000
|
||
Total time: 01:21
|
||
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Loss and accuracy using (cls_best): [0.5931235, tensor(0.7890)]
|
||
Processing data/wiki/ja-100/models/sp15k/qrnn_rnd-nl4.m
|
||
../mldoc/ja-1
|
||
Max vocab: 15000
|
||
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp15k
|
||
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Training
|
||
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/ja.dev.csv
|
||
Data lm, trn: 13500, val: 1500
|
||
Data cls, trn: 1000, val: 1000
|
||
Data tst, trn: 1000, val: 4000
|
||
Size of vocabulary: 15000
|
||
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁、', '▁。', '▁の', '▁に', '▁を', '▁年', 'の', '▁は', '▁・', '▁)']
|
||
Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
|
||
Loading pretrained model
|
||
Unknown tokens 0, first 100: []
|
||
Bptt 70
|
||
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp15k
|
||
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp15k/qrnn_rnd-nl4.m/info.json
|
||
Single training schedule
|
||
epoch train_loss valid_loss accuracy
|
||
1 1.377756 1.402221 0.254000
|
||
2 1.243837 7.998792 0.254000
|
||
3 1.066383 2.645358 0.354000
|
||
4 0.903686 1.348676 0.541000
|
||
5 0.843216 0.945152 0.743000
|
||
6 0.759674 0.801283 0.810000
|
||
7 0.689767 0.786832 0.820000
|
||
8 0.674777 0.778615 0.818000
|
||
Total time: 02:48
|
||
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Loss and accuracy using (cls_best): [0.5008588, tensor(0.8303)]
|
||
Processing data/wiki/ru-100/models/sp15k/qrnn_rnd-nl4.m
|
||
../mldoc/ru-1
|
||
Max vocab: 15000
|
||
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp15k
|
||
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Training
|
||
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/ru.dev.csv
|
||
Running tokenization lm...
|
||
Data lm, trn: 9195, val: 1021
|
||
Running tokenization cls...
|
||
Data cls, trn: 1000, val: 1000
|
||
Running tokenization tst...
|
||
Data tst, trn: 1000, val: 4000
|
||
Size of vocabulary: 15000
|
||
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁в', 'а', 'и', 'е', '▁и', 'й', '▁на', 'х']
|
||
Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
|
||
Loading pretrained model
|
||
Unknown tokens 0, first 100: []
|
||
Bptt 70
|
||
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp15k
|
||
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp15k/qrnn_rnd-nl4.m/info.json
|
||
Single training schedule
|
||
epoch train_loss valid_loss accuracy
|
||
1 1.394592 1.393761 0.265000
|
||
2 1.381886 1.476836 0.293000
|
||
3 1.258016 1.153065 0.555000
|
||
4 1.105392 1.323574 0.556000
|
||
5 0.948704 1.049486 0.703000
|
||
6 0.848964 1.480141 0.605000
|
||
7 0.757975 1.001765 0.723000
|
||
8 0.684587 0.982136 0.741000
|
||
Total time: 03:07
|
||
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Loss and accuracy using (cls_best): [0.7138667, tensor(0.7320)]
|
||
Processing data/wiki/zh-100/models/sp15k/qrnn_rnd-nl4.m
|
||
../mldoc/zh-1
|
||
Max vocab: 15000
|
||
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k
|
||
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Training
|
||
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/zh.dev.csv
|
||
Data lm, trn: 13500, val: 1500
|
||
Data cls, trn: 1000, val: 1000
|
||
Data tst, trn: 1000, val: 4000
|
||
Size of vocabulary: 15000
|
||
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁的', '▁。', '▁年', '▁、', '▁在', '▁一', '▁是', '▁中', '▁有']
|
||
Training args: {'clip': 0.12, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: {'output_p': 0.25, 'hidden_p': 0.1, 'input_p': 0.2, 'embed_p': 0.02, 'weight_p': 0.15}
|
||
Loading pretrained model
|
||
Unknown tokens 0, first 100: []
|
||
Bptt 70
|
||
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k
|
||
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k/qrnn_rnd-nl4.m/info.json
|
||
Single training schedule
|
||
epoch train_loss valid_loss accuracy
|
||
1 1.341714 1.208123 0.569000
|
||
2 1.059330 1.169385 0.662000
|
||
3 0.926222 0.771242 0.824000
|
||
4 0.843994 1.997928 0.524000
|
||
5 0.800537 0.874480 0.756000
|
||
6 0.710552 0.909481 0.758000
|
||
7 0.657595 0.719883 0.854000
|
||
8 0.617662 0.727267 0.852000
|
||
Total time: 02:20
|
||
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k/qrnn_rnd-nl4.m
|
||
Loss and accuracy using (cls_best): [0.48266637, tensor(0.8453)]
|
||
OrderedDict([('data/mldoc/de-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.9024999737739563),
|
||
('data/mldoc/en-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.8149999976158142),
|
||
('data/mldoc/es-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.8964999914169312),
|
||
('data/mldoc/fr-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.8220000267028809),
|
||
('data/mldoc/it-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.7889999747276306),
|
||
('data/mldoc/ja-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.8302500247955322),
|
||
('data/mldoc/ru-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.7319999933242798),
|
||
('data/mldoc/zh-1/models/sp15k/qrnn_rnd-nl4.m',
|
||
0.8452500104904175)])
|
||
data/mldoc/de-1/models/sp15k/qrnn_rnd-nl4.m: 0.9024999737739563
|
||
data/mldoc/en-1/models/sp15k/qrnn_rnd-nl4.m: 0.8149999976158142
|
||
data/mldoc/es-1/models/sp15k/qrnn_rnd-nl4.m: 0.8964999914169312
|
||
data/mldoc/fr-1/models/sp15k/qrnn_rnd-nl4.m: 0.8220000267028809
|
||
data/mldoc/it-1/models/sp15k/qrnn_rnd-nl4.m: 0.7889999747276306
|
||
data/mldoc/ja-1/models/sp15k/qrnn_rnd-nl4.m: 0.8302500247955322
|
||
data/mldoc/ru-1/models/sp15k/qrnn_rnd-nl4.m: 0.7319999933242798
|
||
data/mldoc/zh-1/models/sp15k/qrnn_rnd-nl4.m: 0.8452500104904175
|
||
``` |