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Remove old result logs
This commit is contained in:
Piotr Czapla
@@ -1,26 +0,0 @@
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pretraining
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0 - 8 lost, about 0.30 0.32 after 5 epochs
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8 3.744213 4.021358 0.308377 0.325672
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9 3.700674 4.021499 0.308637 0.325881
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10 3.674045 4.022058 0.308656 0.325903
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--- crash---
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$ python -m ulmfit.train_clas --data_dir data --model_dir data/wiki/wikitext-103/models --pretrain_name=bilm-wt-103 --qrnn=True --name 'concat-2x' --cuda-id=0 --bs 40 --train=True --bidir=True
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Dataset: imdb. Language: en.
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Using QRNNs...
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BiLM
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Loading the pickled data...
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Train size: 22500. Valid size: 2500. Test size: 25000.
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loading encoder
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Starting classifier training
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epoch train_loss valid_loss accuracy
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1 0.346874 0.276838 0.881200
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epoch train_loss valid_loss accuracy
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1 0.321121 0.243946 0.901200
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epoch train_loss valid_loss accuracy
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1 0.303174 0.234627 0.908400
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epoch train_loss valid_loss accuracy
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1 0.295207 0.227533 0.912800
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2 0.269754 0.221328 0.914400
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Saving models at data/wiki/wikitext-103/models
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accuracy: tensor(0.9144)
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@@ -1,20 +0,0 @@
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(fastaiv1) n-waves@GV100:~/workspace/ulmfit-multilingual$ python -m ulmfit.pretrain_lm data/wiki/wikitext-103-unk --qrnn=True --cuda-id=0 -
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-name=bilm-wt-103-unk --num_epochs=10 --bs=64 --bidir=True
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Batch size: 64
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Max vocab: 60000
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Using QRNNs...
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Loading itos: data/wiki/wikitext-103-unk/models/itos_bilm-wt-103-unk.pkl
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Size of vocabulary: 60001
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First 10 words in vocab: the, <pad>, ,, ., of, and, to, in, <eos>, a
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Starting from random weights
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epoch train_loss valid_loss accuracy_fwd accuracy_bwd
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1 4.184118 4.113817 0.308417 0.318290
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2 4.106002 4.039978 0.312220 0.320315
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3 4.160282 4.086650 0.306327 0.314152
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4 4.136789 4.049762 0.309202 0.317373
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5 4.086520 4.001534 0.313158 0.321543
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6 4.036415 3.960494 0.318333 0.325623
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7 3.988382 3.913568 0.324409 0.330398
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8 3.937409 3.874283 0.328386 0.334786
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9 3.912215 3.856325 0.330593 0.337102
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10 3.876535 3.848783 0.331202 0.337649
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@@ -1,20 +0,0 @@
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(fastaiv1) n-waves@GV100:~/workspace/ulmfit-multilingual$ python -m ulmfit.pretrain_lm
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ki/wikitext-103 --qrnn=True --cuda-id=0 --name=bilm-wt-103 --num_epochs=10 --bs=64 --bidir=True
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Batch size: 64
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Max vocab: 60000
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Using QRNNs...
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Loading itos: data/wiki/wikitext-103/models/itos_bilm-wt-103.pkl
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Size of vocabulary: 60001
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First 10 words in vocab: the, <pad>, ,, ., of, and, to, in, <eos>, a
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Starting from random weights
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epoch train_loss valid_loss accuracy_fwd accuracy_bwd
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1 4.141750 4.114931 0.307700 0.320260
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2 4.078711 4.061186 0.310221 0.320550
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3 4.108722 4.081286 0.308383 0.316431
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4 4.054437 4.040497 0.311229 0.319658
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5 4.014880 3.966010 0.318588 0.327607
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6 3.926770 3.897305 0.326874 0.333171
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7 3.855364 3.816452 0.335632 0.342045
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8 3.761600 3.745798 0.343413 0.350675
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10 3.614097 3.687730 0.351651 0.358280
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@@ -1,22 +0,0 @@
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(fastaiv1) pczapla@galatea ~/w/ulmfit-multilingual ❯❯❯ time python -m ulmfit.pretrain_lm data/wiki/wikitext-103 --qrnn=False --cuda-id=1 --name=wt-103 --num_epochs=10 --bs=32
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Batch size: 32
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Max vocab: 60000
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Loading itos: data/wiki/wikitext-103/models/itos_wt-103.pkl
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Size of vocabulary: 60001
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First 10 words in vocab: the, <pad>, ,, ., of, and, to, in, <eos>, a
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Starting from random weights
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epoch train_loss valid_loss accuracy
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1 4.317837 4.245714 0.309034
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2 4.347099 4.251623 0.306932
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3 4.360198 4.302850 0.302014
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4 4.329998 4.264225 0.306828
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5 4.301852 4.209807 0.311763
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6 4.218213 4.131647 0.319867
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7 4.167365 4.047796 0.327259
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8 4.095695 3.980298 0.336255
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9 4.032371 3.919622 0.343671
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10 3.983160 3.906227 0.345863
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Saving models at data/wiki/wikitext-103/models
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Saving optimiser state at data/wiki/wikitext-103/models/lstm3_wt-103_state.pth
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accuracy: tensor(0.3461)
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python -m ulmfit.pretrain_lm data/wiki/wikitext-103 --qrnn=False --cuda-id=1 44147.64s user 16746.69s system 99% cpu 16:58:47.57 total
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@@ -1,23 +0,0 @@
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time python -m ulmfit.pretrain_lm data/wiki/wikitext-103-unk --qrnn=True --cuda-id=0 --name=wt-103 --num_epochs=10 --bs=32
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Batch size: 32
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Max vocab: 60000
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Using QRNNs...
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Loading itos: data/wiki/wikitext-103-unk/models/itos_wt-103.pkl
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Size of vocabulary: 60001
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First 10 words in vocab: the, <pad>, ,, ., of, and, to, in, <eos>, a
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Starting from random weights
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epoch train_loss valid_loss accuracy
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1 4.393613 4.282537 0.305135
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2 4.394575 4.299973 0.300028
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3 4.444056 4.336682 0.295496
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4 4.414292 4.332908 0.297408
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5 4.406248 4.269964 0.302962
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6 4.327769 4.209948 0.309025
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7 4.244819 4.140769 0.315675
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8 4.210000 4.075574 0.323544
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9 4.139524 4.034881 0.328550
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10 4.150556 4.021361 0.331256
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Saving models at data/wiki/wikitext-103-unk/models
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Saving optimiser state at data/wiki/wikitext-103-unk/models/qrnn3_wt-103_state.pth
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accuracy: tensor(0.3312)
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python -m ulmfit.pretrain_lm data/wiki/wikitext-103-unk --qrnn=True --bs=3 32119.72s user 12439.18s system 99% cpu 12:25:03.65 total
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@@ -1,24 +0,0 @@
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ime python -m ulmfit.pretrain_lm data/wiki/wikitext-103-unk --qrnn=True --cuda-id=0 --name=wt-103-wd1 --num_epochs=10 --bs=32
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Batch size: 32
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Max vocab: 60000
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Using QRNNs...
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Saving vocabulary as data/wiki/wikitext-103-unk/models
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Size of vocabulary: 60001
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First 10 words in vocab: the, <pad>, ,, ., of, and, to, in, <eos>, a
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true_wd: True
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Starting from random weights
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epoch train_loss valid_loss accuracy
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1 4.355600 4.271729 0.306827
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2 4.384312 4.288582 0.299482
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3 4.527577 4.366407 0.289836
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4 4.519645 4.387311 0.288076
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5 4.514816 4.371242 0.289862
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6 4.506230 4.337718 0.294208
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7 4.444272 4.295349 0.298786
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8 4.432104 4.257432 0.301785
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9 4.416849 4.242803 0.304147
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10 4.389035 4.239752 0.304871
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Saving models at data/wiki/wikitext-103-unk/models
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Saving optimiser state at data/wiki/wikitext-103-unk/models/qrnn3_wt-103-wd1_state.pth
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itos_fname: data/wiki/wikitext-103-unk/models/itos_wt-103-wd1.pkl
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accuracy: tensor(0.2829)
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@@ -1,20 +0,0 @@
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time python -m ulmfit.pretrain_lm data/wiki/wikitext-103 --qrnn=True --cuda-id=1 --name=wt-103 --num_epochs=10 --bs=32 ✘ 1
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Batch size: 32
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Max vocab: 60000
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Using QRNNs...
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Size of vocabulary: 60001
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First 10 words in vocab: the, <pad>, ,, ., of, and, to, in, <eos>, a
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Saving vocabulary as data/wiki/wikitext-103/models
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epoch train_loss valid_loss accuracy
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1 4.328219 4.268609 0.306414
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2 4.351323 4.282290 0.300560
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3 4.376134 4.345460 0.294145
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4 4.394314 4.319661 0.298142
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5 4.337362 4.265630 0.303437
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6 4.295763 4.199119 0.309354
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7 4.165526 4.121037 0.318062
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8 4.151789 4.060387 0.325899
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9 4.066542 4.014568 0.332732
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10 4.013142 3.997691 0.335299
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Saving models at data/wiki/wikitext-103/models
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Saving optimiser state at data/wiki/wikitext-103/models/qrnn3_wt-103_state.pth
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@@ -1,13 +0,0 @@
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Starting from random weights
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epoch train_loss valid_loss accuracy_fwd accuracy_bwd
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1 3.669261 3.641705 0.399714 0.380689
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2 3.574335 3.547273 0.404729 0.385104
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3 3.573150 3.549644 0.403350 0.384167
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4 3.518714 3.499090 0.408166 0.389015
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5 3.477355 3.441828 0.413880 0.394777
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6 3.408005 3.366269 0.422041 0.402934
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7 3.314280 3.284519 0.431068 0.411727
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8 3.244735 3.205757 0.440180 0.421078
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9 3.170936 3.152495 0.446947 0.428045
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10 3.131996 3.138446 0.448782 0.430013
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Saving optimiser state at data/wiki/wikitext-103/models/sp30k/biqrnn_bs70.m
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