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results.txt
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results.txt
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* TRANSLATE
- english-french TRAIN set
268961it [8:48:57, 8.47it/s]
PRED AVG SCORE: -0.5515, PRED PPL: 1.7358
- english-french DEV set
2000it [03:50, 8.67it/s]
PRED AVG SCORE: -0.5430, PRED PPL: 1.7212
- english-french TEST set
- republican_only
28000it [54:30, 8.56it/s]
PRED AVG SCORE: -0.4400, PRED PPL: 1.5527
- democratic_only
28000it [53:58, 8.65it/s]
PRED AVG SCORE: -0.4409, PRED PPL: 1.5541
* FLIP:
- republican_only.test.fr -> republican_democratic.txt
encoder: french_english.pt
decoder: democratic_generator.pt
27989it [11:09, 41.80it/s]
PRED AVG SCORE: -6.4764, PRED PPL: 649.6345
- democratic_only.test.fr -> democratic_republican.txt
encoder: french_english.pt
decode: republican_generator.pt
27987it [11:21, 41.05it/s]
PRED AVG SCORE: -6.3887, PRED PPL: 595.0680
* CLASSIFY:
- republican_democratic -> Accuracy: 80.43991416309012
- democratic_republican -> Accuracy: 95.63304721030043
* TRAIN:
-$ python train_decoder.py -data ../data/democratic_generator.train.pt -save_model trained_models/democratic_generator -classifier_model ../models/classifier/political_classifier/political_classifier.pt -encoder_model ../models/translation/french_english/french_english.pt -tgt_label 1
Epoch 13, 3900/ 3924; acc: 38.93; ppl: 5.73; closs: 0.0086; 340 src tok/s; 316 tgt tok/s; 193413 s elapsed
100%|████████| 3924/3924 [4:07:04<00:00, 3.74s/it]
Train perplexity: 1.00145
Train accuracy: 42.0701
Validation perplexity: 4.77887
Validation accuracy: 44.0387
Decaying learning rate to 0.015625
-$ python cnn_translate.py \
-gpu 0 \
-model ../models/classifier/political_classifier/political_classifier.pt \
-src ../style_decoder/trained_models/trained_republican_democratic.txt \
-tgt 'democratic' -label0 republican -label1 democratic
Accuracy: 99.77467811158799 - very strange!