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Fix classification scripts and give a way to test accuracy on test set

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This commit is contained in:
Piotr Czapla
2018-12-07 16:10:20 +01:00
parent 4ae2a158a2
commit 50ab34eea9
1 changed files with 6 additions and 6 deletions
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ulmfit/train_clas.py
+6 -6
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@@ -70,7 +70,7 @@ class CLSHyperParams(LMHyperParams):
learn.freeze_to(-2)
learn.fit_one_cycle(1, slice(1e-2 / (2.6 ** 4), 1e-2), moms=(0.8, 0.7))
learn.freeze_to(-3)
learn.fit_one_cycle(2, slice(1e-3 / (2.6 ** 4), 1e-3), moms=(0.8, 0.7))
learn.fit_one_cycle(1, slice(5e-3 / (2.6 ** 4), 5e-3), moms=(0.8, 0.7))
learn.unfreeze()
learn.fit_one_cycle(2, slice(1e-3 / (2.6 ** 4), 1e-3), moms=(0.8, 0.7))
else:
@@ -117,13 +117,13 @@ class CLSHyperParams(LMHyperParams):
if use_test_for_validation:
val_len = max(int(len(tst_df) * 0.1), 2)
tst_len = len(tst_df) - val_len
val_df = trn_df[:tst_len]
val_df = tst_df
cls_cache = 'notst'
else:
val_len = max(int(len(trn_df) * 0.1), 2)
trn_len = len(trn_df) - val_len
trn_df, val_df = trn_df[:trn_len], trn_df[trn_len:]
cls_cache = '.'
if self.tokenizer is Tokenizers.SUBWORD:
#TODO Fix me to make sure it trains correct dictionary
@@ -151,7 +151,7 @@ class CLSHyperParams(LMHyperParams):
try:
if force: raise FileNotFoundError("Forcing reloading of caches")
data_cls = TextClasDataBunch.load(self.cache_dir, '.', bs=bs)
data_cls = TextClasDataBunch.load(self.cache_dir, cls_cache, bs=bs)
print(f"Tokenized data loaded, cls.trn {len(data_cls.train_ds)}, cls.val {len(data_cls.valid_ds)}")
except FileNotFoundError:
args['vocab'] = data_lm.vocab # make sure we use the same vocab for classifcation
@@ -159,7 +159,7 @@ class CLSHyperParams(LMHyperParams):
data_cls = TextClasDataBunch.from_df(path=self.cache_dir, train_df=trn_df, valid_df=val_df,
test_df=tst_df, max_vocab=self.max_vocab, bs=bs, **args)
print(f"Saving tokenized: cls.trn {len(data_cls.train_ds)}, cls.val {len(data_cls.valid_ds)}")
data_cls.save('.')
data_cls.save(cls_cache)
print('Size of vocabulary:', len(data_lm.vocab.itos))
print('First 20 words in vocab:', data_lm.vocab.itos[:20])
return data_cls, data_lm