Bump stanza from 1.7.0 to 1.8.0

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Bumps stanza from 1.7.0 to 1.8.0.

Release notes

Sourced from stanza's releases.

PEFT integration

Integrating PEFT into several different annotators

We integrate PEFT into our training pipeline for several different models. This greatly reduces the size of models with finetuned transformers, letting us make the finetuned versions of those models the default_accurate model.

The biggest gains observed are with the constituency parser and the sentiment classifier.

Previously, the default_accurate package used transformers where the head was trained but the transformer itself was not finetuned.

Model improvements

• POS trained with split optimizer for transformer & non-transformer - unfortunately, did not find settings which consistently improved results stanfordnlp/stanza#1320
• Sentiment trained with peft on the transformer: noticeably improves results for each model. SST scores go from 68 F1 w/ charlm, to 70 F1 w/ transformer, to 74-75 F1 with finetuned or Peft finetuned transformer. stanfordnlp/stanza#1335
• NER also trained with peft: unfortunately, no consistent improvements to scores stanfordnlp/stanza#1336
• depparse includes peft: no consistent improvements yet stanfordnlp/stanza#1337 stanfordnlp/stanza#1344
• Dynamic oracle for top-down constituent parser scheme. Noticeable improvement in the scores for the topdown parser stanfordnlp/stanza#1341
• Constituency parser uses peft: this produces significant improvements, close to the full benefit of finetuning the entire transformer when training constituencies. Example improvement, 87.01 to 88.11 on ID_ICON dataset. stanfordnlp/stanza#1347
• Scripts to build a silver dataset for the constituency parser with filtering of sentences based on model agreement among the sub-models for the ensembles used. Preliminary work indicates an improvement in the benefits of the silver trees, with more work needed to find the optimal parameters used to build the silver dataset. stanfordnlp/stanza#1348
• Lemmatizer ignores goeswith words when training: eliminates words which are a single word, labeled with a single lemma, but split into two words in the UD training data. Typical example would be split email addresses in the EWT training set. stanfordnlp/stanza#1346 stanfordnlp/stanza#1345

Features

• Include SpacesAfter annotations on words in the CoNLL output of documents: stanfordnlp/stanza#1315 stanfordnlp/stanza#1322
• Lemmatizer operates in caseless mode if all of its training data was caseless. Most relevant to the UD Latin treebanks. stanfordnlp/stanza#1331 stanfordnlp/stanza#1330
• wandb support for coref stanfordnlp/stanza#1338
• Coref annotator breaks length ties using POS if available stanfordnlp/stanza#1326 https://github.com/stanfordnlp/stanza/commit/c4c3de5803f27843a5050e10ccae71b3fd9c45e9

Bugfixes

• Using a proxy with download_resources_json was broken: stanfordnlp/stanza#1318 stanfordnlp/stanza#1317 Thank you @​ider-zh
• Fix deprecation warnings for escape sequences: stanfordnlp/stanza#1321 stanfordnlp/stanza#1293 Thank you @​sterliakov
• Coref training rounding error stanfordnlp/stanza#1342
• Top-down constituency models were broken for datasets which did not use ROOT as the top level bracket... this was only DA_Arboretum in practice stanfordnlp/stanza#1354
• V1 of chopping up some longer texts into shorter texts for the transformers to get around length limits. No idea if this actually produces reasonable results for words after the token limit. stanfordnlp/stanza#1350 stanfordnlp/stanza#1294
• Coref prediction off-by-one error for short sentences, was falsely throwing an exception at sentence breaks: stanfordnlp/stanza#1333 stanfordnlp/stanza#1339 https://github.com/stanfordnlp/stanza/commit/f1fbaaad983e58dc3fcf318200d685663fb90737
• Clarify error when a language is only partially handled: https://github.com/stanfordnlp/stanza/commit/da01644b4ba5ba477c36e5d2736012b81bcd00d4 stanfordnlp/stanza#1310

Commits

• 17eb6fc Quieter logging when building a peft wrapper
• e89a7d4 Fix TOP_DOWN parser for da_arboretum, which needs to look at the actual root ...
• 5f18a61 Add the ability to process a few languages with prepare_resources.py
• 363bbec Update sentmient to also have charlm & transformer versions. The transformer...
• 4a7052b Minor logging / typo improvements to conparser
• 3e21404 Initial attempt to chop up long inputs to a transformer into pieces that the ...
• fe45f11 Add a script which filters silver trees by the variance of their scores over ...
• 187850c Only do args['num_generate'] once... possibly fixing a bug where num_generate...
• 8a6c543 Update constituency evaluation to accommodate the per-tree f1
• 837dd03 Add an option to turn off saving the optimizer when saving each constituency ...
• Additional commits viewable in compare view

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Superseded by #305.