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# MLDoc
### Different training schedules
### 1cycle -lstm
```
(fastaiv1) pczapla@galatea ~/w/ulmfit-multilingual ❯❯❯ python -m ulmfit eval --glob="mldoc/*-1/models/sp30k/lstm_nl4.m" --name nl4-1cyc --num-cls-epochs=8 --bs=18 --lr_sched=1cycle ✘ 1
Processing data/mldoc/de-1/models/sp30k/lstm_nl4.m
de-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4-1cyc.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/de.dev.csv
Data lm, trn: 13500, val: 1500
Data cls, trn: 1000, val: 1000
Data tst, trn: 1000, val: 4000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁.', '▁,', '▁der', '▁die', '▁und', '▁in', 'en', "▁&'", 's', '-']
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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.610423 0.287707 0.920000
2 0.390499 0.266688 0.948000
3 0.366716 0.302463 0.933000
4 0.248321 0.305547 0.937000
5 0.166564 0.411075 0.948000
6 0.083940 0.406182 0.950000
7 0.033326 0.388105 0.949000
8 0.014658 0.397507 0.948000
Total time: 06:42
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.3040595, tensor(0.9585)]
Processing data/mldoc/es-1/models/sp30k/lstm_nl4.m
es-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-1cyc.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Data lm, trn: 13013, val: 1445
Data cls, trn: 1000, val: 1000
Data tst, trn: 1000, val: 4000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', '▁en', '▁el', '▁y', 's', '▁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 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.610724 0.278892 0.925000
2 0.372022 0.348428 0.937000
3 0.310411 0.386958 0.927000
4 0.215536 0.273834 0.958000
5 0.163195 0.319600 0.958000
6 0.085268 0.313287 0.961000
7 0.037369 0.347500 0.961000
8 0.016851 0.338436 0.963000
Total time: 05:36
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.31034237, tensor(0.9632)]
Processing data/mldoc/fr-1/models/sp30k/lstm_nl4.m
fr-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4-1cyc.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: 30000
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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.642809 0.240702 0.928000
2 0.420564 0.658542 0.852000
3 0.443345 0.244053 0.927000
4 0.338779 0.335634 0.914000
5 0.224778 0.263748 0.928000
6 0.116705 0.280655 0.944000
7 0.072063 0.287557 0.945000
8 0.048084 0.289200 0.946000
Total time: 06:33
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.29398218, tensor(0.9482)]
Processing data/mldoc/it-1/models/sp30k/lstm_nl4.m
it-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4-1cyc.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: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁di', "▁&'", "'", '▁e', '▁il', '▁la', 'e', '▁in']
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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.736070 0.391008 0.859000
2 0.512531 0.614638 0.860000
3 0.343422 0.594530 0.862000
4 0.370786 0.540225 0.884000
5 0.234727 0.591903 0.892000
6 0.141539 0.589971 0.906000
7 0.073315 0.544248 0.906000
8 0.038477 0.580940 0.904000
Total time: 03:48
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.6642357, tensor(0.8988)]
Processing data/mldoc/ja-1/models/sp30k/lstm_nl4.m
ja-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4-1cyc.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: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁、', '▁の', '▁。', '▁に', '▁を', '▁は', '▁年', '▁が', '▁)', '▁(']
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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.804430 0.435780 0.837000
2 0.576932 0.452903 0.839000
3 0.499791 0.640789 0.806000
4 0.418024 0.610898 0.839000
5 0.259578 0.582953 0.868000
6 0.188161 0.719131 0.888000
7 0.101508 0.766175 0.877000
8 0.072221 0.795415 0.883000
Total time: 08:19
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.636261, tensor(0.9045)]
Processing data/mldoc/ru-1/models/sp30k/lstm_nl4.m
ru-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4-1cyc.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/ru.dev.csv
Data lm, trn: 9195, val: 1021
Data cls, trn: 1000, val: 1000
Data tst, trn: 1000, val: 4000
Size of vocabulary: 30000
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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.821141 0.532432 0.814000
2 0.611059 0.457023 0.866000
3 0.464408 0.484035 0.870000
4 0.446560 0.477454 0.858000
5 0.299095 0.906959 0.858000
6 0.176480 0.709579 0.875000
7 0.089683 0.781081 0.876000
8 0.047031 0.772935 0.877000
Total time: 08:58
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.8528109, tensor(0.8795)]
Processing data/mldoc/zh-1/models/sp30k/lstm_nl4.m
zh-1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k/lstm_nl4-1cyc.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: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁的', '▁。', '▁年', '▁、', '▁在', '▁一', '▁中', '▁人', '▁是']
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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k/lstm_nl4-1cyc.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.696346 0.335083 0.895000
2 0.505075 0.360600 0.906000
3 0.427076 0.462661 0.883000
4 0.351177 0.489026 0.919000
5 0.244958 0.415151 0.918000
6 0.156452 0.494367 0.926000
7 0.085807 0.471611 0.927000
8 0.046887 0.484232 0.929000
Total time: 06:41
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k/lstm_nl4-1cyc.m
Loss and accuracy using (cls_best): [0.50999963, tensor(0.9165)]
OrderedDict([('data/mldoc/de-1/models/sp30k/lstm_nl4-1cyc.m',
0.9585000276565552),
('data/mldoc/es-1/models/sp30k/lstm_nl4-1cyc.m',
0.9632499814033508),
('data/mldoc/fr-1/models/sp30k/lstm_nl4-1cyc.m',
0.9482499957084656),
('data/mldoc/it-1/models/sp30k/lstm_nl4-1cyc.m',
0.8987500071525574),
('data/mldoc/ja-1/models/sp30k/lstm_nl4-1cyc.m',
0.9045000076293945),
('data/mldoc/ru-1/models/sp30k/lstm_nl4-1cyc.m',
0.8794999718666077),
('data/mldoc/zh-1/models/sp30k/lstm_nl4-1cyc.m',
0.9164999723434448)])
data/mldoc/de-1/models/sp30k/lstm_nl4-1cyc.m: 0.9585000276565552
data/mldoc/es-1/models/sp30k/lstm_nl4-1cyc.m: 0.9632499814033508
data/mldoc/fr-1/models/sp30k/lstm_nl4-1cyc.m: 0.9482499957084656
data/mldoc/it-1/models/sp30k/lstm_nl4-1cyc.m: 0.8987500071525574
data/mldoc/ja-1/models/sp30k/lstm_nl4-1cyc.m: 0.9045000076293945
data/mldoc/ru-1/models/sp30k/lstm_nl4-1cyc.m: 0.8794999718666077
data/mldoc/zh-1/models/sp30k/lstm_nl4-1cyc.m: 0.9164999723434448
```
### 2cycle
```bash
python -m ulmfit eval --glob="mldoc/*-1/models/sp15k/qrnn_nl4.m" --name nl4-8e-2cycle --num-cls-epochs=8 --bs=18 --lr_sched=2cycle
Max vocab: 15000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_nl4-8e-2cycle.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Data lm, trn: 13013, val: 1445
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', '▁,', '▁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}
/home/pczapla/anaconda3/envs/fastaiv1/lib/python3.7/site-packages/torch/utils/cpp_extension.py:152: UserWarning:
!! WARNING !!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Your compiler (c++) may be ABI-incompatible with PyTorch!
Please use a compiler that is ABI-compatible with GCC 4.9 and above.
See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
for instructions on how to install GCC 4.9 or higher.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!! WARNING !!
warnings.warn(ABI_INCOMPATIBILITY_WARNING.format(compiler))
Loading pretrained model
Unknown tokens 0, first 100: []
/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_nl4-8e-2cycle.m/info.json
2cycle training schedule
epoch train_loss valid_loss accuracy
1 0.600965 0.232749 0.937000
Total time: 00:07
epoch train_loss valid_loss accuracy
1 0.304946 0.202946 0.946000
2 0.326092 0.207825 0.954000
3 0.286274 0.290416 0.943000
4 0.230937 0.263474 0.950000
5 0.153293 0.293336 0.962000
6 0.080219 0.328380 0.960000
7 0.065156 0.343692 0.961000
8 0.046342 0.367162 0.962000
9 0.028884 0.396987 0.960000
10 0.034997 0.366203 0.960000
Total time: 02:27
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_nl4-8e-2cycle.m
Loss and accuracy using (cls_best): [0.35007542, tensor(0.9528)]
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_nl4-8e-2cycle.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: []
/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_nl4-8e-2cycle.m/info.json
2cycle training schedule
epoch train_loss valid_loss accuracy
1 0.675992 0.460828 0.836000
Total time: 00:09
epoch train_loss valid_loss accuracy
1 0.439060 0.314642 0.888000
2 0.382209 0.374305 0.893000
3 0.338183 0.361669 0.911000
4 0.260323 0.431681 0.901000
5 0.146894 0.597865 0.899000
6 0.090651 0.589435 0.910000
7 0.079902 0.624589 0.918000
8 0.043067 0.558498 0.918000
9 0.022371 0.568702 0.921000
10 0.022498 0.576052 0.922000
Total time: 02:53
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k/qrnn_nl4-8e-2cycle.m
Loss and accuracy using (cls_best): [0.6146808, tensor(0.9150)]
OrderedDict([('data/mldoc/es-1/models/sp15k/qrnn_nl4-8e-2cycle.m',
0.952750027179718),
('data/mldoc/zh-1/models/sp15k/qrnn_nl4-8e-2cycle.m',
0.9150000214576721)])
```
### SIUNGLE 2epochs
```
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: []
/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_nl4-2e-single.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.626836 0.318460 0.912000
2 0.386851 0.327937 0.918000
Total time: 00:34
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k/qrnn_nl4-2e-single.m
Loss and accuracy using (cls_best): [0.32642558, tensor(0.9135)]
OrderedDict([('data/mldoc/es-1/models/sp15k/qrnn_nl4-2e-single.m',
0.9539999961853027),
('data/mldoc/zh-1/models/sp15k/qrnn_nl4-2e-single.m',
0.9135000109672546)])
```
### SINGLE 4epochs
```
OrderedDict([('data/mldoc/es-1/models/sp15k/qrnn_nl4-4e-single.m',
0.9539999961853027),
('data/mldoc/zh-1/models/sp15k/qrnn_nl4-4e-single.m',
0.9210000038146973)])
```
### SINGLE 5 epochs
```
python -m ulmfit eval --glob="mldoc/*-1/models/sp15k/qrnn_nl4.m" --name nl4-5e-single --num-cls-epochs=5 --bs=18 --lr_sched=single
Max vocab: 15000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_nl4-5e-single.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Data lm, trn: 13013, val: 1445
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', '▁,', '▁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}
/home/pczapla/anaconda3/envs/fastaiv1/lib/python3.7/site-packages/torch/utils/cpp_extension.py:152: UserWarning:
!! WARNING !!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Your compiler (c++) may be ABI-incompatible with PyTorch!
Please use a compiler that is ABI-compatible with GCC 4.9 and above.
See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
for instructions on how to install GCC 4.9 or higher.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!! WARNING !!
warnings.warn(ABI_INCOMPATIBILITY_WARNING.format(compiler))
Loading pretrained model
Unknown tokens 0, first 100: []
/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_nl4-5e-single.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.559638 0.250022 0.931000
2 0.366238 0.348553 0.932000
3 0.246830 0.243392 0.954000
4 0.136335 0.242888 0.960000
5 0.106189 0.254603 0.965000
Total time: 01:14
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp15k/qrnn_nl4-5e-single.m
Loss and accuracy using (cls_best): [0.24189772, tensor(0.9588)]
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_nl4-5e-single.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: []
/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_nl4-5e-single.m/info.json
Single training schedule
epoch train_loss valid_loss accuracy
1 0.641053 0.334561 0.891000
2 0.486526 0.374095 0.894000
3 0.309409 0.359222 0.908000
4 0.179104 0.403468 0.920000
5 0.083530 0.414904 0.919000
Total time: 01:24
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp15k/qrnn_nl4-5e-single.m
Loss and accuracy using (cls_best): [0.44048822, tensor(0.9110)]
OrderedDict([('data/mldoc/es-1/models/sp15k/qrnn_nl4-5e-single.m',
0.9587500095367432),
('data/mldoc/zh-1/models/sp15k/qrnn_nl4-5e-single.m',
0.9110000133514404)])
```
#### SINGLE 11epochs
```
Unknown tokens 0, first 100: []
/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_nl4-8e-single.m/info.json
Starting classifier training
Single training schedule
epoch train_loss valid_loss accuracy
1 0.676591 0.205210 0.947000
2 0.402020 0.461279 0.912000
3 0.287975 0.496294 0.921000
4 0.258515 0.243489 0.954000
5 0.219352 0.274136 0.949000
6 0.149339 0.352294 0.956000
7 0.092821 0.378696 0.962000
8 0.055485 0.367379 0.963000
9 0.042695 0.367151 0.964000
10 0.034858 0.386749 0.961000
11 0.021245 0.392899 0.963000
Total time: 02:38
Loss and accuracy using (cls_last): [0.4098273, tensor(0.9595)]
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_nl4-8e-single.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: []
/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_nl4-8e-single.m/info.json
Starting classifier training
Single training schedule
epoch train_loss valid_loss accuracy
1 0.710727 0.355552 0.895000
2 0.523836 0.328691 0.895000
3 0.408339 0.440722 0.894000
4 0.326642 0.422076 0.909000
5 0.217328 0.539624 0.906000
6 0.156753 0.583433 0.912000
7 0.102770 0.549827 0.921000
8 0.053252 0.533528 0.928000
9 0.032845 0.568053 0.927000
10 0.022289 0.604236 0.926000
11 0.015289 0.587667 0.929000
Total time: 03:12
OrderedDict([('data/mldoc/es-1/models/sp15k/qrnn_nl4-8e-single.m',
0.9595000147819519),
('data/mldoc/zh-1/models/sp15k/qrnn_nl4-8e-single.m',
0.9202499985694885)])
```
## Limiit to 100 examples
```
python -m ulmfit eval --glob="mldoc/*-1/models/sp30k/lstm_nl4.m" --name nl4-100e8 --cuda-id=1 --limit=100 --num-cls-epochs=8
{
'data/mldoc/it-1/models/sp30k/lstm_nl4-100e8.m': 0.7799999713897705,
'data/mldoc/de-1/models/sp30k/lstm_nl4-100e8.m': 0.9135000109672546,
'data/mldoc/ja-1/models/sp30k/lstm_nl4-100e8.m': 0.7112500071525574,
'data/mldoc/fr-1/models/sp30k/lstm_nl4-100e8.m': 0.8877500295639038,
'data/mldoc/ru-1/models/sp30k/lstm_nl4-100e8.m': 0.722000002861023,
'data/mldoc/es-1/models/sp30k/lstm_nl4-100e8.m': 0.8169999718666077
}
```
## Noise
```
noise=0.13
lang=de
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
{'data/mldoc/de-1/models/sp30k/lstm_nl4-noise.m': 0.9449999928474426}
noise=0.18
lang=es
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
{'data/mldoc/es-1/models/sp30k/lstm_nl4-noise.m': 0.9312499761581421}
noise=0.18
lang=fr
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
{'data/mldoc/fr-1/models/sp30k/lstm_nl4-noise.m': 0.9049999713897705}
noise=0.27
lang=it
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
{'data/mldoc/it-1/models/sp30k/lstm_nl4-noise.m': 0.8372499942779541}
noise=0.4
lang=ja
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
{'data/mldoc/ja-1/models/sp30k/lstm_nl4-noise.m': 0.7472500205039978
noise=0.32
lang=ru
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
{'data/mldoc/ru-1/models/sp30k/lstm_nl4-noise.m': 0.7567499876022339}
noise=0.28
lang=zh
python -m ulmfit eval --glob="mldoc/${lang}-1/models/sp30k/lstm_nl4.m" --name nl4-noise --cuda-id=1 --num-cls-epochs=2 --noise=${noise}
```
## Fix the sentence piece tokenizer
```
python -m ulmfit eval --glob="mldoc/*-1/models/bsp30k/lstm_nl4.m" --name nl4 --cuda-id=0
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/de.dev.csv
Running tokenization...
Saving tokenized: cls.trn 13500, cls.val 1500
Running tokenization...
Saving tokenized: cls.trn 1000, cls.val 1000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁.', '▁,', '▁der', '▁die', '▁und', '▁in', 'en', "▁&'", 's', '-']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.480367 0.263987 0.930000
epoch train_loss valid_loss accuracy
1 0.340463 0.209449 0.940000
epoch train_loss valid_loss accuracy
1 0.235290 0.214566 0.952000
epoch train_loss valid_loss accuracy
1 0.169588 0.217762 0.952000
2 0.175439 0.215570 0.946000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4.m
Loss and accuracy using (cls_best): [0.15467079, tensor(0.9563)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Running tokenization...
Saving tokenized: cls.trn 13013, cls.val 1445
Running tokenization...
Saving tokenized: cls.trn 1000, cls.val 1000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', '▁en', '▁el', '▁y', 's', '▁a', '▁que']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.609305 0.343920 0.914000
epoch train_loss valid_loss accuracy
1 0.380833 0.204708 0.947000
epoch train_loss valid_loss accuracy
1 0.311563 0.210382 0.943000
epoch train_loss valid_loss accuracy
1 0.266655 0.192309 0.955000
2 0.235553 0.183249 0.953000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4.m
Loss and accuracy using (cls_best): [0.19250762, tensor(0.9427)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/fr.dev.csv
Running tokenization...
Saving tokenized: cls.trn 13500, cls.val 1500
Running tokenization...
Saving tokenized: cls.trn 1000, cls.val 1000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁.', "'", 's', '▁la', '▁le', '▁et', '▁l', '▁à']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.527443 0.342664 0.901000
epoch train_loss valid_loss accuracy
1 0.359752 0.203693 0.936000
epoch train_loss valid_loss accuracy
1 0.272514 0.188933 0.938000
epoch train_loss valid_loss accuracy
1 0.191520 0.183208 0.938000
2 0.201412 0.178796 0.942000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4.m
Loss and accuracy using (cls_best): [0.18170285, tensor(0.9420)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/it.dev.csv
Running tokenization...
Saving tokenized: cls.trn 13500, cls.val 1500
Running tokenization...
Saving tokenized: cls.trn 1000, cls.val 1000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁di', "▁&'", "'", '▁e', '▁il', '▁la', 'e', '▁in']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.754286 0.599928 0.783000
epoch train_loss valid_loss accuracy
1 0.501399 0.379078 0.851000
epoch train_loss valid_loss accuracy
1 0.408768 0.345188 0.867000
epoch train_loss valid_loss accuracy
1 0.324877 0.335110 0.872000
2 0.291118 0.336596 0.879000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4.m
Loss and accuracy using (cls_best): [0.33244577, tensor(0.8852)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4.m
Evaluating previously trained model
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/ja.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', '<unk>', '▁', '▁、', '▁の', '▁。', '▁に', '▁を', '▁は', '▁年', '▁が', '▁)', '▁(']
Loss and accuracy using (cls_last): [0.330675, tensor(0.8873)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4.m
Evaluating previously trained model
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/ru.dev.csv
Tokenized data loaded, lm.trn 9195, lm.val 1021
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', '<unk>', '▁', '▁,', '▁.', '▁в', 'а', '▁и', 'е', 'и', 'й', '▁на', 'х']
Loss and accuracy using (cls_last): [0.3987146, tensor(0.8680)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k/lstm_nl4.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/zh.dev.csv
Running tokenization...
Saving tokenized: cls.trn 13500, cls.val 1500
Running tokenization...
Saving tokenized: cls.trn 1000, cls.val 1000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁的', '▁。', '▁年', '▁、', '▁在', '▁一', '▁中', '▁人', '▁是']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k/lstm_nl4.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.612067 0.487164 0.860000
epoch train_loss valid_loss accuracy
1 0.441519 0.343330 0.886000
epoch train_loss valid_loss accuracy
1 0.384575 0.318655 0.897000
epoch train_loss valid_loss accuracy
1 0.298987 0.305157 0.899000
2 0.293190 0.312572 0.901000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/zh-1/models/sp30k/lstm_nl4.m
Loss and accuracy using (cls_best): [0.28432375, tensor(0.9047)]
OrderedDict([('data/mldoc/de-1/models/sp30k/lstm_nl4.m', 0.956250011920929),
('data/mldoc/es-1/models/sp30k/lstm_nl4.m', 0.9427499771118164),
('data/mldoc/fr-1/models/sp30k/lstm_nl4.m', 0.9419999718666077),
('data/mldoc/it-1/models/sp30k/lstm_nl4.m', 0.8852499723434448),
('data/mldoc/ja-1/models/sp30k/lstm_nl4.m', 0.8872500061988831),
('data/mldoc/ru-1/models/sp30k/lstm_nl4.m', 0.8679999709129333),
('data/mldoc/zh-1/models/sp30k/lstm_nl4.m', 0.9047499895095825)])
--- Additonal run on ru
python -m ulmfit eval --glob="mldoc/ru-1/models/bsp30k/lstm_nl4.m" --name nl4 --cuda-id=0 ✘ 1
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/ru.dev.csv
Running tokenization...
Saving tokenized: cls.trn 9195, cls.val 1021
Running tokenization...
Saving tokenized: cls.trn 1000, cls.val 1000
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁в', 'а', '▁и', 'е', 'и', 'й', '▁на', 'х']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.814752 0.555627 0.808000
epoch train_loss valid_loss accuracy
1 0.659532 0.427135 0.855000
epoch train_loss valid_loss accuracy
1 0.508609 0.427321 0.851000
epoch train_loss valid_loss accuracy
1 0.440108 0.396991 0.872000
2 0.440024 0.388976 0.866000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4.m
Loss and accuracy using (cls_best): [0.3959306, tensor(0.8685)]
----
----
python -m ulmfit eval --glob="mldoc/es-1/models/bsp30k/lstm_nl4.m" --name nl4-2nd --cuda-id=0
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-2nd.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Tokenized data loaded, lm.trn 13013, lm.val 1445
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', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', '▁en', '▁el', '▁y', 's', '▁a', '▁que']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/bsp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/bsp30k/lstm_nl4.m/../itos')], 'pretrained_model': None, 'alpha': 2, 'beta': 1, 'drop_mult': 0.3} dps: [0.25 0.1 0.2 0.02 0.15]
Unknown tokens 0, first 100: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-2nd.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 0.654984 0.453887 0.818000
epoch train_loss valid_loss accuracy
1 0.451552 0.220058 0.934000
epoch train_loss valid_loss accuracy
1 0.323974 0.193342 0.949000
epoch train_loss valid_loss accuracy
1 0.244755 0.201804 0.945000
2 0.237175 0.183736 0.953000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-2nd.m
Loss and accuracy using (cls_best): [0.18296617, tensor(0.9480)]
OrderedDict([('data/mldoc/es-1/models/sp30k/lstm_nl4-2nd.m',
0.9480000138282776)])
----
```
### LIMIT LOgs
```
python -m ulmfit eval --name nl4-100e8 --cuda-id=1 --limit=100 --num-cls-epochs=8 ✘ 130
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4-100e8.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/it.dev.csv
Tokenized data loaded, lm.trn 13500, lm.val 1500
Limiting data set to: 100
Tokenized data loaded, cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁di', "▁&'", "'", '▁e', '▁il', '▁la', 'e', '▁in']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4-100e8.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.214805 1.382632 0.280000
epoch train_loss valid_loss accuracy
1 0.977314 1.269534 0.450000
epoch train_loss valid_loss accuracy
1 0.856274 1.223441 0.530000
epoch train_loss valid_loss accuracy
1 0.718223 1.188048 0.620000
2 0.735718 1.130525 0.730000
3 0.730894 1.069027 0.710000
4 0.715334 1.015253 0.710000
5 0.716080 0.965223 0.720000
6 0.695554 0.918456 0.730000
7 0.689949 0.892840 0.730000
8 0.675208 0.876222 0.720000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/it-1/models/sp30k/lstm_nl4-100e8.m
Loss and accuracy using (cls_best): [0.7090041, tensor(0.7800)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4-100e8.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/de.dev.csv
Tokenized data loaded, lm.trn 13500, lm.val 1500
Limiting data set to: 100
Running tokenization...
Saving tokenized: cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁.', '▁,', '▁der', '▁die', '▁und', '▁in', 'en', "▁&'", 's', '-']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4-100e8.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.141527 1.328262 0.280000
epoch train_loss valid_loss accuracy
1 0.703434 1.170250 0.510000
epoch train_loss valid_loss accuracy
1 0.568693 1.051980 0.780000
epoch train_loss valid_loss accuracy
1 0.455238 0.990438 0.800000
2 0.475659 0.928943 0.850000
3 0.477652 0.848537 0.920000
4 0.455583 0.769415 0.930000
5 0.450824 0.690618 0.930000
6 0.443699 0.633900 0.940000
7 0.430881 0.563667 0.950000
8 0.419999 0.524655 0.950000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/de-1/models/sp30k/lstm_nl4-100e8.m
Loss and accuracy using (cls_best): [0.45835665, tensor(0.9135)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4-100e8.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/ja.dev.csv
Tokenized data loaded, lm.trn 13500, lm.val 1500
Limiting data set to: 100
Tokenized data loaded, cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁、', '▁の', '▁。', '▁に', '▁を', '▁は', '▁年', '▁が', '▁)', '▁(']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4-100e8.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.342269 1.399389 0.230000
epoch train_loss valid_loss accuracy
1 0.957341 1.344665 0.280000
epoch train_loss valid_loss accuracy
1 0.881869 1.301798 0.450000
epoch train_loss valid_loss accuracy
1 0.887575 1.280226 0.440000
2 0.835731 1.257639 0.450000
3 0.813987 1.219512 0.510000
4 0.792665 1.181309 0.520000
5 0.785690 1.151372 0.510000
6 0.784095 1.152232 0.500000
7 0.768115 1.133895 0.520000
8 0.769684 1.124231 0.530000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ja-1/models/sp30k/lstm_nl4-100e8.m
Loss and accuracy using (cls_best): [0.8863698, tensor(0.7113)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4-100e8.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/fr.dev.csv
Tokenized data loaded, lm.trn 13500, lm.val 1500
Limiting data set to: 100
Running tokenization...
Saving tokenized: cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁.', "'", 's', '▁la', '▁le', '▁et', '▁l', '▁à']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4-100e8.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.220506 1.413276 0.200000
epoch train_loss valid_loss accuracy
1 0.791777 1.306999 0.290000
epoch train_loss valid_loss accuracy
1 0.572241 1.190053 0.580000
epoch train_loss valid_loss accuracy
1 0.502800 1.130456 0.710000
2 0.515115 1.056434 0.770000
3 0.522720 0.974482 0.780000
4 0.518296 0.881002 0.840000
5 0.496588 0.825646 0.880000
6 0.490416 0.771587 0.860000
7 0.497172 0.722874 0.850000
8 0.491894 0.682278 0.850000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/fr-1/models/sp30k/lstm_nl4-100e8.m
Loss and accuracy using (cls_best): [0.5428351, tensor(0.8878)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4-100e8.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/ru.dev.csv
Tokenized data loaded, lm.trn 9195, lm.val 1021
Limiting data set to: 100
Running tokenization...
Saving tokenized: cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁,', '▁.', '▁в', 'а', '▁и', 'е', 'и', 'й', '▁на', 'х']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4-100e8.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.367201 1.409767 0.240000
epoch train_loss valid_loss accuracy
1 1.099071 1.320811 0.330000
epoch train_loss valid_loss accuracy
1 0.875845 1.253172 0.410000
epoch train_loss valid_loss accuracy
1 0.775657 1.215067 0.580000
2 0.774420 1.171324 0.660000
3 0.766028 1.118901 0.680000
4 0.744478 1.074021 0.680000
5 0.738797 1.033736 0.660000
6 0.733380 0.997304 0.660000
7 0.723470 0.977280 0.670000
8 0.710699 0.953586 0.640000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/ru-1/models/sp30k/lstm_nl4-100e8.m
Loss and accuracy using (cls_best): [0.8535175, tensor(0.7220)]
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-100e8.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Tokenized data loaded, lm.trn 13013, lm.val 1445
Limiting data set to: 100
Running tokenization...
Saving tokenized: cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', '▁en', '▁el', '▁y', 's', '▁a', '▁que']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-100e8.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.142170 1.330161 0.300000
epoch train_loss valid_loss accuracy
1 0.767807 1.212253 0.420000
epoch train_loss valid_loss accuracy
1 0.636803 1.099303 0.540000
epoch train_loss valid_loss accuracy
1 0.584241 0.997207 0.610000
2 0.578480 0.907674 0.710000
3 0.548451 0.830268 0.730000
4 0.535560 0.762040 0.750000
5 0.522172 0.746566 0.740000
6 0.506584 0.676038 0.770000
7 0.493665 0.651112 0.770000
8 0.493031 0.621689 0.770000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-100e8.m
Loss and accuracy using (cls_best): [0.54911107, tensor(0.8170)]
{'data/mldoc/it-1/models/sp30k/lstm_nl4-100e8.m': 0.7799999713897705, 'data/mldoc/de-1/models/sp30k/lstm_nl4-100e8.m': 0.9135000109672546, 'data/mldoc/ja-1/models/sp30k/lstm_nl4-100e8.m': 0.7112500071525574, 'data/mldoc/fr-1/models/sp30k/lstm_nl4-100e8.m': 0.8877500295639038, 'data/mldoc/ru-1/models/sp30k/lstm_nl4-100e8.m': 0.722000002861023, 'data/mldoc/es-1/models/sp30k/lstm_nl4-100e8.m': 0.8169999718666077}
python -m ulmfit eval --glob="mldoc/es-1/models/sp30k/lstm_nl4.m" --name nl4-100-2nd --cuda-id=1 --num-cls-epochs=8 --limit=100
Max vocab: 30000
Cache dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Model dir: /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-100-2nd.m
Training
Loading validation /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/es.dev.csv
Tokenized data loaded, lm.trn 13013, lm.val 1445
Limiting data set to: 100
Tokenized data loaded, cls.trn 100, cls.val 100
Size of vocabulary: 30000
First 20 words in vocab: ['xxunk', 'xxpad', 'xxbos', 'xxfld', 'xxmaj', 'xxup', 'xxrep', 'xxwrep', '<unk>', '▁', '▁de', '▁,', '▁la', '▁.', '▁en', '▁el', '▁y', 's', '▁a', '▁que']
Training args: {'tie_weights': True, 'clip': 0.12, 'bptt': 70, 'pretrained_fnames': [PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4.m/lm_best'), PosixPath('/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/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: []
/home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k
Saving info /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-100-2nd.m/info.json
Starting classifier training
epoch train_loss valid_loss accuracy
1 1.243127 1.354496 0.290000
epoch train_loss valid_loss accuracy
1 0.840900 1.213333 0.460000
epoch train_loss valid_loss accuracy
1 0.656407 1.055138 0.750000
epoch train_loss valid_loss accuracy
1 0.558013 0.983957 0.780000
2 0.554590 0.915244 0.750000
3 0.536740 0.840074 0.770000
4 0.521179 0.759908 0.790000
5 0.515218 0.692961 0.810000
6 0.500587 0.639504 0.810000
7 0.486596 0.593410 0.840000
8 0.472318 0.550126 0.830000
Saving models at /home/pczapla/workspace/ulmfit-multilingual/data/mldoc/es-1/models/sp30k/lstm_nl4-100-2nd.m
Loss and accuracy using (cls_best): [0.5382241, tensor(0.8332)]
{'data/mldoc/es-1/models/sp30k/lstm_nl4-100-2nd.m': 0.8332499861717224}
```
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