update
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- .gitattributes +1 -0
- .gitignore +187 -0
- .pre-commit-config.yaml +19 -0
- LICENSE +201 -0
- Makefile +26 -0
- README.md +136 -6
- conf/Pretrain_excluded.yaml +51 -0
- conf/Pretrain_v1.5.yaml +51 -0
- conf/Pretrain_v1.5_woInstruction.yaml +51 -0
- conf/Pretrain_woOverlapV2.yaml +51 -0
- conf/ac/g1_dpspd.yaml +18 -0
- conf/ac/g1_dpspd_fp16.yaml +18 -0
- conf/cadec.yaml +3 -0
- conf/hyperred.yaml +3 -0
- conf/merge_all_data.yaml +6 -0
- conf/merge_analysis_data.yaml +18 -0
- conf/merge_analysis_data_woInstruction.yaml +18 -0
- conf/merge_uie_data.yaml +18 -0
- conf/mirror-ace05en.yaml +70 -0
- conf/mirror-multi-task-pretrain.yaml +51 -0
- conf/mrc.yaml +43 -0
- conf/ner.yaml +45 -0
- conf/nlu/cola.yaml +6 -0
- conf/nlu/mnli.yaml +6 -0
- conf/nlu/mrpc.yaml +3 -0
- conf/nlu/plm.yaml +19 -0
- conf/nlu/qnli.yaml +6 -0
- conf/nlu/qqp.yaml +6 -0
- conf/nlu/rte.yaml +6 -0
- conf/nlu/squad_v2.yaml +4 -0
- conf/nlu/sst-2.yaml +6 -0
- conf/t-rex_pretrain.yaml +9 -0
- conf/uie_data/absa_14lap.yaml +3 -0
- conf/uie_data/absa_14res.yaml +3 -0
- conf/uie_data/absa_15res.yaml +3 -0
- conf/uie_data/absa_16res.yaml +3 -0
- conf/uie_data/ent_ace04.yaml +3 -0
- conf/uie_data/ent_ace05.yaml +3 -0
- conf/uie_data/ent_conll03.yaml +3 -0
- conf/uie_data/event_ace05.yaml +3 -0
- conf/uie_data/event_casie.yaml +3 -0
- conf/uie_data/fewshot.yaml +5 -0
- conf/uie_data/merged.yaml +3 -0
- conf/uie_data/rel_ace05.yaml +3 -0
- conf/uie_data/rel_conll04.yaml +3 -0
- conf/uie_data/rel_nyt.yaml +3 -0
- conf/uie_data/rel_scierc.yaml +3 -0
- conf/uie_data/wPretrain.yaml +19 -0
- eval.py +0 -0
- index.html +288 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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figs/mirror-frontpage.png filter=lfs diff=lfs merge=lfs -text
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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.scrapy
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docs/_build/
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.pybuilder/
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target/
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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.DS_Store
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._.DS_Store
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debug.py
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outputs/
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resources/NER/msra/cache/
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resources/NER/msra/mrc/
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resources/NER/msra/formatted/
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resources/MRC/cmrc2018/cache/
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resources/MRC/cmrc2018/formatted/
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cache/*.cache
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resources/MRC/DuReader-*/
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resources/**/*.json
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resources/**/*.jsonl
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resources/**/*.zip
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resources/**/*.tsv
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resources/**/*.xml
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resources/**/raw/
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resources.tar.gz
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debug/
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debug.json
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mirror_outputs/
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sampled_stats.xlsx
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mirror_fewshot_outputs/
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conll03-100.jsonl
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tmp*/
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resources/
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.pre-commit-config.yaml
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repos:
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- repo: https://github.com/pycqa/isort
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rev: 5.12.0
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hooks:
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- id: isort
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name: isort (python)
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args: ["--profile", "black", "--filter-files"]
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- repo: https://github.com/psf/black
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rev: 22.12.0
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hooks:
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- id: black
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.4.0
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hooks:
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- id: trailing-whitespace
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- id: end-of-file-fixer
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- id: check-yaml
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- id: check-added-large-files
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args: [--maxkb=900]
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LICENSE
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Apache License
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Version 2.0, January 2004
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http://www.apache.org/licenses/
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TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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1. Definitions.
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"License" shall mean the terms and conditions for use, reproduction,
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"control" means (i) the power, direct or indirect, to cause the
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direction or management of such entity, whether by contract or
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"You" (or "Your") shall mean an individual or Legal Entity
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|
README.md
CHANGED
@@ -1,13 +1,143 @@
|
|
1 |
---
|
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title: Mirror
|
3 |
-
emoji:
|
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colorFrom:
|
5 |
-
colorTo:
|
6 |
sdk: gradio
|
7 |
sdk_version: 4.1.2
|
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app_file: app.py
|
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pinned:
|
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license: apache-2.0
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---
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-
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|
1 |
---
|
2 |
title: Mirror
|
3 |
+
emoji: 🪞
|
4 |
+
colorFrom: blue
|
5 |
+
colorTo: yellow
|
6 |
sdk: gradio
|
7 |
sdk_version: 4.1.2
|
8 |
+
app_file: src/app/gradio_app.py
|
9 |
+
pinned: true
|
10 |
license: apache-2.0
|
11 |
---
|
12 |
|
13 |
+
<div align="center">
|
14 |
+
<h1>🪞 Mirror: A Universal Framework for Various Information Extraction Tasks</h1>
|
15 |
+
<img src="figs/mirror-frontpage.png" width="300" alt="Magic mirror"><br>
|
16 |
+
<i>Image generated by DALLE 3</i><br>
|
17 |
+
<!-- <img src="figs/mirror-framework.png" alt="Mirror Framework"> -->
|
18 |
+
<a href="https://arxiv.org/abs/2311.05419" target="_blank">[Paper]</a> | <a href="https://huggingface.co/spaces/Spico/Mirror" target="_blank">[Demo]</a><br>
|
19 |
+
📃 Our paper has been accepted to EMNLP23 main conference, <a href="http://arxiv.org/abs/2311.05419" target="_blank">check it out</a>!<br>
|
20 |
+
</div>
|
21 |
+
|
22 |
+
<hr>
|
23 |
+
|
24 |
+
😎: This is the official implementation of [🪞Mirror](https://arxiv.org/abs/2311.05419) which supports *almost* all the Information Extraction tasks.
|
25 |
+
|
26 |
+
The name, Mirror, comes from the classical story *Snow White and the Seven Dwarfs*, where a magic mirror knows everything in the world.
|
27 |
+
We aim to build such a powerful tool for the IE community.
|
28 |
+
|
29 |
+
## 🔥 Supported Tasks
|
30 |
+
|
31 |
+
1. Named Entity Recognition
|
32 |
+
2. Entity Relationship Extraction (Triplet Extraction)
|
33 |
+
3. Event Extraction
|
34 |
+
4. Aspect-based Sentiment Analysis
|
35 |
+
5. Multi-span Extraction (e.g. Discontinuous NER)
|
36 |
+
6. N-ary Extraction (e.g. Hyper Relation Extraction)
|
37 |
+
7. Extractive Machine Reading Comprehension (MRC) and Question Answering
|
38 |
+
8. Classification & Multi-choice MRC
|
39 |
+
|
40 |
+
![System Comparison](figs/sys-comparison.png)
|
41 |
+
|
42 |
+
## 🌴 Dependencies
|
43 |
+
|
44 |
+
Python>=3.10
|
45 |
+
|
46 |
+
```bash
|
47 |
+
pip install -r requirements.txt
|
48 |
+
```
|
49 |
+
|
50 |
+
## 🚀 QuickStart
|
51 |
+
|
52 |
+
### Pretrained Model Weights & Datasets
|
53 |
+
|
54 |
+
Download the pretrained model weights & datasets from [[OSF]](https://osf.io/kwsm4/?view_only=5b66734d88cf456b93f17b6bac8a44fb) .
|
55 |
+
|
56 |
+
No worries, it's an anonymous link just for double blind peer reviewing.
|
57 |
+
|
58 |
+
### Pretraining
|
59 |
+
|
60 |
+
1. Download and unzip the pretraining corpus into `resources/Mirror/v1.4_sampled_v3/merged/all_excluded`
|
61 |
+
2. Start to run
|
62 |
+
|
63 |
+
```bash
|
64 |
+
CUDA_VISIBLE_DEVICES=0 rex train -m src.task -dc conf/Pretrain_excluded.yaml
|
65 |
+
```
|
66 |
+
|
67 |
+
### Fine-tuning
|
68 |
+
|
69 |
+
⚠️ Due to data license constraints, some datasets are unavailable to provide directly (e.g. ACE04, ACE05).
|
70 |
+
|
71 |
+
1. Download and unzip the pretraining corpus into `resources/Mirror/v1.4_sampled_v3/merged/all_excluded`
|
72 |
+
2. Download and unzip the fine-tuning datasets into `resources/Mirror/uie/`
|
73 |
+
3. Start to fine-tuning
|
74 |
+
|
75 |
+
```bash
|
76 |
+
# UIE tasks
|
77 |
+
CUDA_VISIBLE_DEVICES=0 bash scripts/single_task_wPTAllExcluded_wInstruction/run1.sh
|
78 |
+
CUDA_VISIBLE_DEVICES=1 bash scripts/single_task_wPTAllExcluded_wInstruction/run2.sh
|
79 |
+
CUDA_VISIBLE_DEVICES=2 bash scripts/single_task_wPTAllExcluded_wInstruction/run3.sh
|
80 |
+
CUDA_VISIBLE_DEVICES=3 bash scripts/single_task_wPTAllExcluded_wInstruction/run4.sh
|
81 |
+
# Multi-span and N-ary extraction
|
82 |
+
CUDA_VISIBLE_DEVICES=4 bash scripts/single_task_wPTAllExcluded_wInstruction/run_new_tasks.sh
|
83 |
+
# GLUE datasets
|
84 |
+
CUDA_VISIBLE_DEVICES=5 bash scripts/single_task_wPTAllExcluded_wInstruction/glue.sh
|
85 |
+
```
|
86 |
+
|
87 |
+
### Analysis Experiments
|
88 |
+
|
89 |
+
- Few-shot experiments : `scripts/run_fewshot.sh`. Collecting results: `python mirror_fewshot_outputs/get_avg_results.py`
|
90 |
+
- Mirror w/ PT w/o Inst. : `scripts/single_task_wPTAllExcluded_woInstruction`
|
91 |
+
- Mirror w/o PT w/ Inst. : `scripts/single_task_wo_pretrain`
|
92 |
+
- Mirror w/o PT w/o Inst. : `scripts/single_task_wo_pretrain_wo_instruction`
|
93 |
+
|
94 |
+
### Evaluation
|
95 |
+
|
96 |
+
1. Change `task_dir` and `data_pairs` you want to evaluate. The default setting is to get results of Mirror<sub>direct</sub> on all downstream tasks.
|
97 |
+
2. `CUDA_VISIBLE_DEVICES=0 python -m src.eval`
|
98 |
+
|
99 |
+
### Demo
|
100 |
+
|
101 |
+
1. Download and unzip the pretrained task dump into `mirror_outputs/Mirror_Pretrain_AllExcluded_2`
|
102 |
+
2. Try our demo:
|
103 |
+
|
104 |
+
```bash
|
105 |
+
CUDA_VISIBLE_DEVICES=0 python -m src.app.api_backend
|
106 |
+
```
|
107 |
+
|
108 |
+
![Demo](figs/mirror-demo.gif)
|
109 |
+
|
110 |
+
## 📋 Citation
|
111 |
+
|
112 |
+
```bibtex
|
113 |
+
@misc{zhu_mirror_2023,
|
114 |
+
shorttitle = {Mirror},
|
115 |
+
title = {Mirror: A Universal Framework for Various Information Extraction Tasks},
|
116 |
+
author = {Zhu, Tong and Ren, Junfei and Yu, Zijian and Wu, Mengsong and Zhang, Guoliang and Qu, Xiaoye and Chen, Wenliang and Wang, Zhefeng and Huai, Baoxing and Zhang, Min},
|
117 |
+
url = {http://arxiv.org/abs/2311.05419},
|
118 |
+
doi = {10.48550/arXiv.2311.05419},
|
119 |
+
urldate = {2023-11-10},
|
120 |
+
publisher = {arXiv},
|
121 |
+
month = nov,
|
122 |
+
year = {2023},
|
123 |
+
note = {arXiv:2311.05419 [cs]},
|
124 |
+
keywords = {Computer Science - Artificial Intelligence, Computer Science - Computation and Language},
|
125 |
+
}
|
126 |
+
```
|
127 |
+
|
128 |
+
## 🛣️ Roadmap
|
129 |
+
|
130 |
+
- [ ] Convert current model into Huggingface version, supporting loading from `transformers` like other newly released LLMs.
|
131 |
+
- [ ] Remove `Background` area, merge `TL`, `TP` into a single `T` token
|
132 |
+
- [ ] Add more task data: keyword extraction, coreference resolution, FrameNet, WikiNER, T-Rex relation extraction dataset, etc.
|
133 |
+
- [ ] Pre-train on all the data (including benchmarks) to build a nice out-of-the-box toolkit for universal IE.
|
134 |
+
|
135 |
+
## 💌 Yours sincerely
|
136 |
+
|
137 |
+
This project is licensed under Apache-2.0.
|
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We hope you enjoy it ~
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<hr>
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+
<div align="center">
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<p>Mirror Team w/ 💖</p>
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</div>
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conf/Pretrain_excluded.yaml
ADDED
@@ -0,0 +1,51 @@
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1 |
+
# task
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task_type: SchemaGuidedInstructBertTask
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3 |
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task_name: Mirror_Pretrain_AllExcluded_2
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4 |
+
comment: '~~content as label, (start, end + 1) span'
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5 |
+
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6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
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8 |
+
debug_mode: false
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9 |
+
label_span: tag # tag `[LM]` or content `person`
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10 |
+
mode: span # w2 (1,2,3) or span (1,3)
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11 |
+
stream_mode: false
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12 |
+
|
13 |
+
# filepaths
|
14 |
+
plm_dir: microsoft/deberta-v3-large
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15 |
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data_dir: resources/Mirror/v1.4_sampled_v3/merged/all_excluded
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16 |
+
output_dir: mirror_outputs
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17 |
+
task_dir: ${output_dir}/${task_name}
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18 |
+
train_filepath: ${data_dir}/train.jsonl
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19 |
+
dev_filepath: ${data_dir}/dev.jsonl
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20 |
+
test_filepath: ${data_dir}/test.jsonl
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21 |
+
dump_cache_dir: ${task_dir}/cache
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22 |
+
regenerate_cache: false
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23 |
+
|
24 |
+
# training
|
25 |
+
random_seed: 1227
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26 |
+
base_model_path: null
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27 |
+
eval_on_data: [train]
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28 |
+
select_best_on_data: train
|
29 |
+
select_best_by_key: loss
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30 |
+
final_eval_on_test: false
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31 |
+
save_every_ckpt: true
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32 |
+
save_best_ckpt: true
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33 |
+
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34 |
+
warmup_proportion: 0.1
|
35 |
+
num_epochs: 3
|
36 |
+
epoch_patience: -1
|
37 |
+
num_steps: -1
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38 |
+
step_patience: -1
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39 |
+
step_eval_interval: 10000
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40 |
+
train_batch_size: 8
|
41 |
+
eval_batch_size: 8
|
42 |
+
grad_accum_steps: 1
|
43 |
+
learning_rate: !!float 2e-5
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44 |
+
other_learning_rate: !!float 1e-4
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45 |
+
max_grad_norm: 1.0
|
46 |
+
weight_decay: 0.1
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47 |
+
|
48 |
+
# model
|
49 |
+
dropout: 0.3
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50 |
+
use_rope: true
|
51 |
+
biaffine_size: 512
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conf/Pretrain_v1.5.yaml
ADDED
@@ -0,0 +1,51 @@
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1 |
+
# task
|
2 |
+
task_type: SchemaGuidedInstructBertTask
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3 |
+
task_name: Mirror_Pretrain_DataV1.5_2
|
4 |
+
comment: '~~content as label, (start, end + 1) span'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
|
8 |
+
debug_mode: false
|
9 |
+
label_span: tag # tag `[LM]` or content `person`
|
10 |
+
mode: span # w2 (1,2,3) or span (1,3)
|
11 |
+
stream_mode: false
|
12 |
+
|
13 |
+
# filepaths
|
14 |
+
plm_dir: microsoft/deberta-v3-large
|
15 |
+
data_dir: resources/Mirror/v1.5/merged/t-rex-200k
|
16 |
+
output_dir: mirror_outputs
|
17 |
+
task_dir: ${output_dir}/${task_name}
|
18 |
+
train_filepath: ${data_dir}/train.jsonl
|
19 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
20 |
+
test_filepath: ${data_dir}/test.jsonl
|
21 |
+
dump_cache_dir: ${task_dir}/cache
|
22 |
+
regenerate_cache: false
|
23 |
+
|
24 |
+
# training
|
25 |
+
random_seed: 1227
|
26 |
+
base_model_path: null
|
27 |
+
eval_on_data: [train]
|
28 |
+
select_best_on_data: train
|
29 |
+
select_best_by_key: loss
|
30 |
+
final_eval_on_test: false
|
31 |
+
save_every_ckpt: true
|
32 |
+
save_best_ckpt: true
|
33 |
+
|
34 |
+
warmup_proportion: 0.1
|
35 |
+
num_epochs: 3
|
36 |
+
epoch_patience: -1
|
37 |
+
num_steps: -1
|
38 |
+
step_patience: -1
|
39 |
+
step_eval_interval: 10000
|
40 |
+
train_batch_size: 8
|
41 |
+
eval_batch_size: 8
|
42 |
+
grad_accum_steps: 1
|
43 |
+
learning_rate: !!float 2e-5
|
44 |
+
other_learning_rate: !!float 1e-4
|
45 |
+
max_grad_norm: 1.0
|
46 |
+
weight_decay: 0.1
|
47 |
+
|
48 |
+
# model
|
49 |
+
dropout: 0.3
|
50 |
+
use_rope: true
|
51 |
+
biaffine_size: 512
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conf/Pretrain_v1.5_woInstruction.yaml
ADDED
@@ -0,0 +1,51 @@
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|
1 |
+
# task
|
2 |
+
task_type: SchemaGuidedInstructBertTask
|
3 |
+
task_name: Mirror_Pretrain_DataV1.5_woInstruction
|
4 |
+
comment: '~~content as label, (start, end + 1) span'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
|
8 |
+
debug_mode: false
|
9 |
+
label_span: tag # tag `[LM]` or content `person`
|
10 |
+
mode: span # w2 (1,2,3) or span (1,3)
|
11 |
+
stream_mode: false
|
12 |
+
|
13 |
+
# filepaths
|
14 |
+
plm_dir: microsoft/deberta-v3-large
|
15 |
+
data_dir: resources/Mirror/v1.5/merged/t-rex-200k-woInstruction/remove_instruction
|
16 |
+
output_dir: mirror_outputs
|
17 |
+
task_dir: ${output_dir}/${task_name}
|
18 |
+
train_filepath: ${data_dir}/train.jsonl
|
19 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
20 |
+
test_filepath: ${data_dir}/test.jsonl
|
21 |
+
dump_cache_dir: ${task_dir}/cache
|
22 |
+
regenerate_cache: false
|
23 |
+
|
24 |
+
# training
|
25 |
+
random_seed: 1227
|
26 |
+
base_model_path: null
|
27 |
+
eval_on_data: [train]
|
28 |
+
select_best_on_data: train
|
29 |
+
select_best_by_key: loss
|
30 |
+
final_eval_on_test: false
|
31 |
+
save_every_ckpt: true
|
32 |
+
save_best_ckpt: true
|
33 |
+
|
34 |
+
warmup_proportion: 0.1
|
35 |
+
num_epochs: 3
|
36 |
+
epoch_patience: -1
|
37 |
+
num_steps: -1
|
38 |
+
step_patience: -1
|
39 |
+
step_eval_interval: 10000
|
40 |
+
train_batch_size: 8
|
41 |
+
eval_batch_size: 8
|
42 |
+
grad_accum_steps: 1
|
43 |
+
learning_rate: !!float 2e-5
|
44 |
+
other_learning_rate: !!float 1e-4
|
45 |
+
max_grad_norm: 1.0
|
46 |
+
weight_decay: 0.1
|
47 |
+
|
48 |
+
# model
|
49 |
+
dropout: 0.3
|
50 |
+
use_rope: true
|
51 |
+
biaffine_size: 512
|
conf/Pretrain_woOverlapV2.yaml
ADDED
@@ -0,0 +1,51 @@
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|
1 |
+
# task
|
2 |
+
task_type: SchemaGuidedInstructBertTask
|
3 |
+
task_name: Mirror_Pretrain_woOverlapV2
|
4 |
+
comment: '~~content as label, (start, end + 1) span'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
|
8 |
+
debug_mode: false
|
9 |
+
label_span: tag # tag `[LM]` or content `person`
|
10 |
+
mode: span # w2 (1,2,3) or span (1,3)
|
11 |
+
stream_mode: false
|
12 |
+
|
13 |
+
# filepaths
|
14 |
+
plm_dir: microsoft/deberta-v3-large
|
15 |
+
data_dir: resources/Mirror/v1.4_sampled_v3/merged/all
|
16 |
+
output_dir: mirror_outputs
|
17 |
+
task_dir: ${output_dir}/${task_name}
|
18 |
+
train_filepath: ${data_dir}/train_wo_overlap_v2.jsonl
|
19 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
20 |
+
test_filepath: ${data_dir}/test.jsonl
|
21 |
+
dump_cache_dir: ${task_dir}/cache
|
22 |
+
regenerate_cache: false
|
23 |
+
|
24 |
+
# training
|
25 |
+
random_seed: 1227
|
26 |
+
base_model_path: null
|
27 |
+
eval_on_data: [train]
|
28 |
+
select_best_on_data: train
|
29 |
+
select_best_by_key: loss
|
30 |
+
final_eval_on_test: false
|
31 |
+
save_every_ckpt: true
|
32 |
+
save_best_ckpt: true
|
33 |
+
|
34 |
+
warmup_proportion: 0.1
|
35 |
+
num_epochs: 3
|
36 |
+
epoch_patience: -1
|
37 |
+
num_steps: -1
|
38 |
+
step_patience: -1
|
39 |
+
step_eval_interval: 10000
|
40 |
+
train_batch_size: 8
|
41 |
+
eval_batch_size: 8
|
42 |
+
grad_accum_steps: 1
|
43 |
+
learning_rate: !!float 2e-5
|
44 |
+
other_learning_rate: !!float 1e-4
|
45 |
+
max_grad_norm: 1.0
|
46 |
+
weight_decay: 0.1
|
47 |
+
|
48 |
+
# model
|
49 |
+
dropout: 0.3
|
50 |
+
use_rope: true
|
51 |
+
biaffine_size: 512
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conf/ac/g1_dpspd.yaml
ADDED
@@ -0,0 +1,18 @@
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|
1 |
+
compute_environment: LOCAL_MACHINE
|
2 |
+
deepspeed_config:
|
3 |
+
gradient_accumulation_steps: 1
|
4 |
+
zero3_init_flag: false
|
5 |
+
zero_stage: 1
|
6 |
+
distributed_type: DEEPSPEED
|
7 |
+
downcast_bf16: 'no'
|
8 |
+
machine_rank: 0
|
9 |
+
main_training_function: main
|
10 |
+
mixed_precision: 'no'
|
11 |
+
num_machines: 1
|
12 |
+
num_processes: 1
|
13 |
+
rdzv_backend: static
|
14 |
+
same_network: true
|
15 |
+
tpu_env: []
|
16 |
+
tpu_use_cluster: false
|
17 |
+
tpu_use_sudo: false
|
18 |
+
use_cpu: false
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conf/ac/g1_dpspd_fp16.yaml
ADDED
@@ -0,0 +1,18 @@
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|
1 |
+
compute_environment: LOCAL_MACHINE
|
2 |
+
deepspeed_config:
|
3 |
+
gradient_accumulation_steps: 4
|
4 |
+
zero3_init_flag: false
|
5 |
+
zero_stage: 1
|
6 |
+
distributed_type: DEEPSPEED
|
7 |
+
downcast_bf16: 'no'
|
8 |
+
machine_rank: 0
|
9 |
+
main_training_function: main
|
10 |
+
mixed_precision: fp16
|
11 |
+
num_machines: 1
|
12 |
+
num_processes: 1
|
13 |
+
rdzv_backend: static
|
14 |
+
same_network: true
|
15 |
+
tpu_env: []
|
16 |
+
tpu_use_cluster: false
|
17 |
+
tpu_use_sudo: false
|
18 |
+
use_cpu: false
|
conf/cadec.yaml
ADDED
@@ -0,0 +1,3 @@
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|
1 |
+
task_name: Mirror_SingleTask_DiscontinuousNER_CADEC
|
2 |
+
data_dir: resources/Mirror/new_abilities_v2/cadec/new
|
3 |
+
best_metric_field: discontinuous_ent.micro.f1
|
conf/hyperred.yaml
ADDED
@@ -0,0 +1,3 @@
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|
1 |
+
task_name: Mirror_SingleTask_HyperRel_HyperRED
|
2 |
+
data_dir: resources/Mirror/new_abilities_v2/HyperRED/new
|
3 |
+
best_metric_field: hyper_rel.micro.f1
|
conf/merge_all_data.yaml
ADDED
@@ -0,0 +1,6 @@
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|
1 |
+
task_name: InstructBert_MergedAllData
|
2 |
+
data_dir: resources/Mirror/v1.3/merged_pretrained_data
|
3 |
+
train_filepath: ${data_dir}/train.jsonl
|
4 |
+
dev_filepath: resources/Mirror/v1.3/uie_data/dev.jsonl
|
5 |
+
test_filepath: resources/Mirror/v1.3/uie_data/test.jsonl
|
6 |
+
num_epochs: 1
|
conf/merge_analysis_data.yaml
ADDED
@@ -0,0 +1,18 @@
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|
1 |
+
task_name: Mirror_MultiTask_Analysis
|
2 |
+
plm_dir: microsoft/deberta-v3-large
|
3 |
+
|
4 |
+
data_dir: resources/Mirror/uie/merged_analysis
|
5 |
+
train_filepath: ${data_dir}/train.jsonl
|
6 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
7 |
+
test_filepath: ${data_dir}/test.jsonl
|
8 |
+
num_epochs: 20
|
9 |
+
epoch_patience: 3
|
10 |
+
regenerate_cache: true
|
11 |
+
|
12 |
+
eval_on_data: [dev]
|
13 |
+
select_best_on_data: dev
|
14 |
+
select_best_by_key: metric
|
15 |
+
best_metric_field: general_spans.micro.f1
|
16 |
+
final_eval_on_test: true
|
17 |
+
|
18 |
+
base_model_path: null
|
conf/merge_analysis_data_woInstruction.yaml
ADDED
@@ -0,0 +1,18 @@
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|
1 |
+
task_name: Mirror_MultiTask_Analysis_woInstruction
|
2 |
+
plm_dir: microsoft/deberta-v3-large
|
3 |
+
|
4 |
+
data_dir: resources/Mirror/uie/merged_analysis/remove_instruction
|
5 |
+
train_filepath: ${data_dir}/train.jsonl
|
6 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
7 |
+
test_filepath: ${data_dir}/test.jsonl
|
8 |
+
num_epochs: 20
|
9 |
+
epoch_patience: 3
|
10 |
+
regenerate_cache: true
|
11 |
+
|
12 |
+
eval_on_data: [dev]
|
13 |
+
select_best_on_data: dev
|
14 |
+
select_best_by_key: metric
|
15 |
+
best_metric_field: general_spans.micro.f1
|
16 |
+
final_eval_on_test: true
|
17 |
+
|
18 |
+
base_model_path: null
|
conf/merge_uie_data.yaml
ADDED
@@ -0,0 +1,18 @@
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_woPT_NewMergedUIEData_woOverlap
|
2 |
+
plm_dir: microsoft/deberta-v3-large
|
3 |
+
|
4 |
+
data_dir: resources/Mirror/uie/merged
|
5 |
+
train_filepath: ${data_dir}/train_wo_overlap.jsonl
|
6 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
7 |
+
test_filepath: ${data_dir}/test.jsonl
|
8 |
+
num_epochs: 20
|
9 |
+
epoch_patience: 3
|
10 |
+
regenerate_cache: true
|
11 |
+
|
12 |
+
eval_on_data: [dev]
|
13 |
+
select_best_on_data: dev
|
14 |
+
select_best_by_key: metric
|
15 |
+
best_metric_field: general_spans.micro.f1
|
16 |
+
final_eval_on_test: true
|
17 |
+
|
18 |
+
base_model_path: null
|
conf/mirror-ace05en.yaml
ADDED
@@ -0,0 +1,70 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# task
|
2 |
+
task_type: SchemaGuidedInstructBertTask
|
3 |
+
task_name: InstructBert_TagSpan_DebertaV3Base_ACE05ENPlus
|
4 |
+
comment: '~~content as label, (start, end + 1) span'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
|
8 |
+
debug_mode: false
|
9 |
+
label_span: tag # tag `[LM]` or content `person`
|
10 |
+
mode: span # w2 (1,2,3) or span (1,3)
|
11 |
+
|
12 |
+
# filepaths
|
13 |
+
plm_dir: microsoft/deberta-v3-base
|
14 |
+
# plm_dir: bert-base-cased
|
15 |
+
# data_dir: resources/Mirror/Tasks/EE/ACE05-EN
|
16 |
+
# data_dir: resources/Mirror/Tasks/RE/merged-20230502-2340-v1
|
17 |
+
# data_dir: resources/Mirror/Tasks/RE/merged-20230502-2358-v2-woADE
|
18 |
+
# data_dir: resources/Mirror/Tasks/EE/ACE05-EN-labelmap
|
19 |
+
data_dir: resources/Mirror/v1.3/event/en/ACE05-EN-plus/fixed_instructed
|
20 |
+
output_dir: outputs
|
21 |
+
task_dir: ${output_dir}/${task_name}
|
22 |
+
# train_filepath: ${data_dir}/ACE2005_plus_train.jsonl
|
23 |
+
# dev_filepath: ${data_dir}/ACE2005_plus_dev.jsonl
|
24 |
+
# test_filepath: ${data_dir}/ACE2005_plus_test.jsonl
|
25 |
+
# train_filepath: ${data_dir}/ACE2005_oneie_NER_train.jsonl
|
26 |
+
# dev_filepath: ${data_dir}/ACE2005_oneie_NER_dev.jsonl
|
27 |
+
# test_filepath: ${data_dir}/ACE2005_oneie_NER_test.jsonl
|
28 |
+
# train_filepath: ${data_dir}/ACE2005_oneie_RE_train.jsonl
|
29 |
+
# dev_filepath: ${data_dir}/ACE2005_oneie_RE_dev.jsonl
|
30 |
+
# test_filepath: ${data_dir}/ACE2005_oneie_RE_test.jsonl
|
31 |
+
# train_filepath: ${data_dir}/ACE2005_oneie_EE_train.jsonl
|
32 |
+
# dev_filepath: ${data_dir}/ACE2005_oneie_EE_dev.jsonl
|
33 |
+
# test_filepath: ${data_dir}/ACE2005_oneie_EE_test.jsonl
|
34 |
+
# train_filepath: ${data_dir}/ACE2005_oneie_train.jsonl
|
35 |
+
# dev_filepath: ${data_dir}/ACE2005_oneie_dev.jsonl
|
36 |
+
# test_filepath: ${data_dir}/ACE2005_oneie_test.jsonl
|
37 |
+
# train_filepath: ${data_dir}/train.jsonl
|
38 |
+
# dev_filepath: ${data_dir}/dev.jsonl
|
39 |
+
# test_filepath: ${data_dir}/test.jsonl
|
40 |
+
train_filepath: ${data_dir}/train.jsonl
|
41 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
42 |
+
test_filepath: ${data_dir}/test.jsonl
|
43 |
+
|
44 |
+
dump_cache_dir: ${task_dir}/cache
|
45 |
+
regenerate_cache: false
|
46 |
+
|
47 |
+
# training
|
48 |
+
random_seed: 1227
|
49 |
+
eval_on_data: [dev, test]
|
50 |
+
select_best_on_data: dev
|
51 |
+
select_best_by_key: metric
|
52 |
+
best_metric_field: general_spans.micro.f1
|
53 |
+
final_eval_on_test: true
|
54 |
+
save_every_ckpt: false
|
55 |
+
save_best_ckpt: true
|
56 |
+
|
57 |
+
warmup_proportion: 0.1
|
58 |
+
num_epochs: 50
|
59 |
+
epoch_patience: 5
|
60 |
+
train_batch_size: 32
|
61 |
+
eval_batch_size: 32
|
62 |
+
learning_rate: !!float 3e-5
|
63 |
+
other_learning_rate: !!float 3e-5
|
64 |
+
max_grad_norm: 1.0
|
65 |
+
weight_decay: 0.1
|
66 |
+
|
67 |
+
# model
|
68 |
+
dropout: 0.3
|
69 |
+
use_rope: true
|
70 |
+
biaffine_size: 512
|
conf/mirror-multi-task-pretrain.yaml
ADDED
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# task
|
2 |
+
task_type: SchemaGuidedInstructBertTask
|
3 |
+
task_name: MirrorLarge_SamplingPretrain_woLowResource_woOverlap
|
4 |
+
comment: '~~content as label, (start, end + 1) span'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
|
8 |
+
debug_mode: false
|
9 |
+
label_span: tag # tag `[LM]` or content `person`
|
10 |
+
mode: span # w2 (1,2,3) or span (1,3)
|
11 |
+
stream_mode: false
|
12 |
+
|
13 |
+
# filepaths
|
14 |
+
plm_dir: microsoft/deberta-v3-large
|
15 |
+
data_dir: resources/Mirror/v1.4_sampled_v3/merged/woLowResource
|
16 |
+
output_dir: mirror_outputs
|
17 |
+
task_dir: ${output_dir}/${task_name}
|
18 |
+
train_filepath: ${data_dir}/train_wo_overlap.jsonl
|
19 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
20 |
+
test_filepath: ${data_dir}/test.jsonl
|
21 |
+
dump_cache_dir: ${task_dir}/cache
|
22 |
+
regenerate_cache: false
|
23 |
+
|
24 |
+
# training
|
25 |
+
random_seed: 1227
|
26 |
+
base_model_path: null
|
27 |
+
eval_on_data: [train]
|
28 |
+
select_best_on_data: train
|
29 |
+
select_best_by_key: loss
|
30 |
+
final_eval_on_test: false
|
31 |
+
save_every_ckpt: true
|
32 |
+
save_best_ckpt: true
|
33 |
+
|
34 |
+
warmup_proportion: 0.1
|
35 |
+
num_epochs: 1
|
36 |
+
epoch_patience: -1
|
37 |
+
num_steps: -1
|
38 |
+
step_patience: -1
|
39 |
+
step_eval_interval: 3000
|
40 |
+
train_batch_size: 8
|
41 |
+
eval_batch_size: 8
|
42 |
+
grad_accum_steps: 1
|
43 |
+
learning_rate: !!float 2e-5
|
44 |
+
other_learning_rate: !!float 1e-4
|
45 |
+
max_grad_norm: 1.0
|
46 |
+
weight_decay: 0.1
|
47 |
+
|
48 |
+
# model
|
49 |
+
dropout: 0.3
|
50 |
+
use_rope: true
|
51 |
+
biaffine_size: 512
|
conf/mrc.yaml
ADDED
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# task
|
2 |
+
task_type: MrcQaTask
|
3 |
+
task_name: Mirror_RobertaBaseWwm_Cons_MsraMrc
|
4 |
+
comment: 'GlobalPointer with RoPE'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 512
|
8 |
+
debug_mode: false
|
9 |
+
mode: cons
|
10 |
+
|
11 |
+
# filepaths
|
12 |
+
plm_dir: hfl/chinese-roberta-wwm-ext
|
13 |
+
data_dir: resources/NER/msra/mrc
|
14 |
+
output_dir: outputs
|
15 |
+
task_dir: ${output_dir}/${task_name}
|
16 |
+
train_filepath: ${data_dir}/train.jsonl
|
17 |
+
dev_filepath: ${data_dir}/test.jsonl
|
18 |
+
test_filepath: ${data_dir}/test.jsonl
|
19 |
+
dump_cache_dir: ${task_dir}/cache
|
20 |
+
regenerate_cache: true
|
21 |
+
|
22 |
+
# training
|
23 |
+
random_seed: 1227
|
24 |
+
eval_on_data: [dev]
|
25 |
+
select_best_on_data: dev
|
26 |
+
select_best_by_key: metric
|
27 |
+
best_metric_field: micro.f1
|
28 |
+
final_eval_on_test: true
|
29 |
+
|
30 |
+
warmup_proportion: 0.1
|
31 |
+
step_eval_interval: 20000
|
32 |
+
step_patience: -1
|
33 |
+
num_epochs: 5
|
34 |
+
epoch_patience: 5
|
35 |
+
train_batch_size: 32
|
36 |
+
eval_batch_size: 64
|
37 |
+
learning_rate: !!float 5e-5
|
38 |
+
other_learning_rate: !!float 1e-4
|
39 |
+
max_grad_norm: 1.0
|
40 |
+
|
41 |
+
# model
|
42 |
+
dropout: 0.3
|
43 |
+
biaffine_size: 512
|
conf/ner.yaml
ADDED
@@ -0,0 +1,45 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# task
|
2 |
+
task_type: MrcTaggingTask
|
3 |
+
task_name: debug-Mirror_W2_MSRAv2_NER_FreezeBertEmbAnd0-3_bs64
|
4 |
+
comment: 'bert mrc w/ w2ner for NER'
|
5 |
+
|
6 |
+
# data preprocessing
|
7 |
+
max_seq_len: 300
|
8 |
+
negative_sample_prob: 1.0
|
9 |
+
debug_mode: false
|
10 |
+
mode: w2
|
11 |
+
|
12 |
+
# filepaths
|
13 |
+
base_model_path: outputs/RobertaBase_data20230314v2/ckpt/MrcGlobalPointerModel.best.pth
|
14 |
+
plm_dir: hfl/chinese-roberta-wwm-ext
|
15 |
+
data_dir: resources/NER/MSRA_v2/formatted
|
16 |
+
output_dir: outputs
|
17 |
+
task_dir: ${output_dir}/${task_name}
|
18 |
+
train_filepath: ${data_dir}/train.char.bmes.jsonl
|
19 |
+
dev_filepath: ${data_dir}/dev.char.bmes.jsonl
|
20 |
+
test_filepath: ${data_dir}/test.char.bmes.jsonl
|
21 |
+
ent_type2query_filepath: ${data_dir}/query.json
|
22 |
+
dump_cache_dir: ${task_dir}/cache
|
23 |
+
regenerate_cache: true
|
24 |
+
|
25 |
+
# training
|
26 |
+
random_seed: 1227
|
27 |
+
eval_on_data: [dev, test]
|
28 |
+
select_best_on_data: dev
|
29 |
+
select_best_by_key: metric
|
30 |
+
best_metric_field: micro.f1
|
31 |
+
final_eval_on_test: true
|
32 |
+
|
33 |
+
warmup_proportion: 0.1
|
34 |
+
num_epochs: 5
|
35 |
+
epoch_patience: 5
|
36 |
+
train_batch_size: 64
|
37 |
+
eval_batch_size: 128
|
38 |
+
learning_rate: !!float 5e-5
|
39 |
+
other_learning_rate: !!float 1e-4
|
40 |
+
max_grad_norm: 1.0
|
41 |
+
weight_decay: 0.1
|
42 |
+
|
43 |
+
# model
|
44 |
+
dropout: 0.3
|
45 |
+
biaffine_size: 512
|
conf/nlu/cola.yaml
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_CoLA
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/CoLA/formated
|
3 |
+
train_filepath: ${data_dir}/train.jsonl
|
4 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
5 |
+
test_filepath: ${data_dir}/dev.jsonl
|
6 |
+
best_metric_field: cls.mcc
|
conf/nlu/mnli.yaml
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_MNLI
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/MNLI/formated
|
3 |
+
train_filepath: ${data_dir}/MNLI_train.jsonl
|
4 |
+
dev_filepath: ${data_dir}/MNLI_dev.jsonl
|
5 |
+
test_filepath: ${data_dir}/MNLI_dev.jsonl
|
6 |
+
best_metric_field: cls.acc
|
conf/nlu/mrpc.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_MRPC
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/MRPC/formated
|
3 |
+
best_metric_field: cls.acc
|
conf/nlu/plm.yaml
ADDED
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
plm_dir: microsoft/deberta-v3-large
|
2 |
+
base_model_path: mirror_outputs/Mirror_Pretrain_AllExcluded_2/ckpt/SchemaGuidedInstructBertModel.best.pth
|
3 |
+
|
4 |
+
stream_mode: false
|
5 |
+
train_filepath: ${data_dir}/train.jsonl
|
6 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
7 |
+
test_filepath: ${data_dir}/test.jsonl
|
8 |
+
|
9 |
+
num_epochs: 5
|
10 |
+
epoch_patience: -1
|
11 |
+
num_steps: -1
|
12 |
+
step_patience: -1
|
13 |
+
step_eval_interval: -1
|
14 |
+
|
15 |
+
eval_on_data: [dev]
|
16 |
+
select_best_on_data: dev
|
17 |
+
select_best_by_key: metric
|
18 |
+
best_metric_field: general_spans.micro.f1
|
19 |
+
final_eval_on_test: true
|
conf/nlu/qnli.yaml
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_QNLI
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/QNLI/processed
|
3 |
+
train_filepath: ${data_dir}/QNLI_train.jsonl
|
4 |
+
dev_filepath: ${data_dir}/QNLI_dev.jsonl
|
5 |
+
test_filepath: ${data_dir}/QNLI_dev.jsonl
|
6 |
+
best_metric_field: cls.acc
|
conf/nlu/qqp.yaml
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_QQP
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/QQP/new
|
3 |
+
train_filepath: ${data_dir}/train.jsonl
|
4 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
5 |
+
test_filepath: ${data_dir}/dev.jsonl
|
6 |
+
best_metric_field: cls.acc
|
conf/nlu/rte.yaml
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_RTE
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/RTE/formated
|
3 |
+
train_filepath: ${data_dir}/RTE_train.jsonl
|
4 |
+
dev_filepath: ${data_dir}/RTE_dev.jsonl
|
5 |
+
test_filepath: ${data_dir}/RTE_dev.jsonl
|
6 |
+
best_metric_field: cls.acc
|
conf/nlu/squad_v2.yaml
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_MRC_SQuADv2
|
2 |
+
data_dir: resources/Mirror/v1.3/span/en/squad_v2
|
3 |
+
test_filepath: ${data_dir}/dev.jsonl
|
4 |
+
best_metric_field: span.f1.f1
|
conf/nlu/sst-2.yaml
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Cls_SST2
|
2 |
+
data_dir: resources/Mirror/v1.3/cls/en/SST-2/instructed
|
3 |
+
train_filepath: ${data_dir}/SST-2_train.jsonl
|
4 |
+
dev_filepath: ${data_dir}/SST-2_dev.jsonl
|
5 |
+
test_filepath: ${data_dir}/SST-2_dev.jsonl
|
6 |
+
best_metric_field: cls.acc
|
conf/t-rex_pretrain.yaml
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
task_name: InstructBert_TagSpan_DebertaV3Base_TRExPretrain
|
2 |
+
data_dir: resources/Mirror/v1.3/rel/en/T-REx/instructed
|
3 |
+
train_filepath: ${data_dir}/t-rex.udi.fix.jsonl
|
4 |
+
|
5 |
+
num_epochs: 3
|
6 |
+
eval_on_data: [train]
|
7 |
+
select_best_on_data: train
|
8 |
+
select_best_by_key: loss
|
9 |
+
final_eval_on_test: false
|
conf/uie_data/absa_14lap.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_ABSA_14lap
|
2 |
+
data_dir: resources/Mirror/uie/absa/14lap
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/absa_14res.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_ABSA_14res
|
2 |
+
data_dir: resources/Mirror/uie/absa/14res
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/absa_15res.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_ABSA_15res
|
2 |
+
data_dir: resources/Mirror/uie/absa/15res
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/absa_16res.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_ABSA_16res
|
2 |
+
data_dir: resources/Mirror/uie/absa/16res
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/ent_ace04.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Ent_ACE04
|
2 |
+
data_dir: resources/Mirror/uie/ent/ace04
|
3 |
+
best_metric_field: ent.micro.f1
|
conf/uie_data/ent_ace05.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Ent_ACE05
|
2 |
+
data_dir: resources/Mirror/uie/ent/ace05
|
3 |
+
best_metric_field: ent.micro.f1
|
conf/uie_data/ent_conll03.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Ent_CoNLL03
|
2 |
+
data_dir: resources/Mirror/uie/ent/conll03
|
3 |
+
best_metric_field: ent.micro.f1
|
conf/uie_data/event_ace05.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Event_ACE05
|
2 |
+
data_dir: resources/Mirror/uie/event/ace05-evt
|
3 |
+
best_metric_field: event.arg_cls.f1
|
conf/uie_data/event_casie.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Event_CASIE
|
2 |
+
data_dir: resources/Mirror/uie/event/casie
|
3 |
+
best_metric_field: event.arg_cls.f1
|
conf/uie_data/fewshot.yaml
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
num_epochs: 200
|
2 |
+
epoch_patience: 10
|
3 |
+
output_dir: mirror_fewshot_outputs
|
4 |
+
base_model_path: mirror_outputs/Mirror_Pretrain_AllExcluded_2/ckpt/SchemaGuidedInstructBertModel.best.pth
|
5 |
+
save_every_ckpt: false
|
conf/uie_data/merged.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_MultiTask_UIE
|
2 |
+
data_dir: resources/Mirror/uie/merged
|
3 |
+
best_metric_field: general_spans.micro.f1
|
conf/uie_data/rel_ace05.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Rel_ACE05
|
2 |
+
data_dir: resources/Mirror/uie/rel/ace05-rel
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/rel_conll04.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Rel_CoNLL04
|
2 |
+
data_dir: resources/Mirror/uie/rel/conll04
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/rel_nyt.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Rel_NYT
|
2 |
+
data_dir: resources/Mirror/uie/rel/nyt
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/rel_scierc.yaml
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
task_name: Mirror_SingleTask_Rel_SciERC
|
2 |
+
data_dir: resources/Mirror/uie/rel/scierc
|
3 |
+
best_metric_field: rel.rel.micro.f1
|
conf/uie_data/wPretrain.yaml
ADDED
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
plm_dir: microsoft/deberta-v3-large
|
2 |
+
base_model_path: mirror_outputs/Mirror_Pretrain_AllExcluded_2/ckpt/SchemaGuidedInstructBertModel.best.pth
|
3 |
+
|
4 |
+
stream_mode: false
|
5 |
+
train_filepath: ${data_dir}/train.jsonl
|
6 |
+
dev_filepath: ${data_dir}/dev.jsonl
|
7 |
+
test_filepath: ${data_dir}/test.jsonl
|
8 |
+
|
9 |
+
num_epochs: 20
|
10 |
+
epoch_patience: 3
|
11 |
+
num_steps: -1
|
12 |
+
step_patience: -1
|
13 |
+
step_eval_interval: -1
|
14 |
+
|
15 |
+
eval_on_data: [dev]
|
16 |
+
select_best_on_data: dev
|
17 |
+
select_best_by_key: metric
|
18 |
+
best_metric_field: general_spans.micro.f1
|
19 |
+
final_eval_on_test: true
|
eval.py
ADDED
File without changes
|
index.html
ADDED
@@ -0,0 +1,288 @@
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
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|
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|
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|
|
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|
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|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
<!DOCTYPE html>
|
2 |
+
<html lang="en">
|
3 |
+
|
4 |
+
<head>
|
5 |
+
<meta charset="UTF-8">
|
6 |
+
<meta http-equiv="X-UA-Compatible" content="IE=edge">
|
7 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
8 |
+
<title>🪞Mirror</title>
|
9 |
+
<link rel="stylesheet" href="https://unpkg.com/boltcss/bolt.min.css">
|
10 |
+
<script type="importmap">
|
11 |
+
{
|
12 |
+
"imports": {
|
13 |
+
"vue": "https://unpkg.com/vue@3/dist/vue.esm-browser.js"
|
14 |
+
}
|
15 |
+
}
|
16 |
+
</script>
|
17 |
+
<style>
|
18 |
+
body {
|
19 |
+
max-width: 800px;
|
20 |
+
margin: 40px auto;
|
21 |
+
padding: 0 20px;
|
22 |
+
}
|
23 |
+
|
24 |
+
.form-group {
|
25 |
+
display: flex;
|
26 |
+
flex-direction: row;
|
27 |
+
justify-content: flex-start;
|
28 |
+
align-items: center;
|
29 |
+
}
|
30 |
+
|
31 |
+
label {
|
32 |
+
margin-right: 1rem;
|
33 |
+
}
|
34 |
+
|
35 |
+
button {
|
36 |
+
margin: 0.2rem 0.2rem;
|
37 |
+
}
|
38 |
+
|
39 |
+
button:hover {
|
40 |
+
background-color: #dbdbdb;
|
41 |
+
}
|
42 |
+
|
43 |
+
footer {
|
44 |
+
text-align: center;
|
45 |
+
margin-top: 2rem;
|
46 |
+
}
|
47 |
+
|
48 |
+
input {
|
49 |
+
width: 100%;
|
50 |
+
}
|
51 |
+
|
52 |
+
.button-group {
|
53 |
+
margin-top: 1rem;
|
54 |
+
margin-bottom: 1rem;
|
55 |
+
}
|
56 |
+
|
57 |
+
.submit-button {
|
58 |
+
background-color: #ffc83d;
|
59 |
+
color: #d67d00;
|
60 |
+
font-weight: bold;
|
61 |
+
}
|
62 |
+
|
63 |
+
.lc-button {
|
64 |
+
background-color: #c4e5be;
|
65 |
+
}
|
66 |
+
|
67 |
+
.lm-button {
|
68 |
+
background-color: #dae7fb;
|
69 |
+
}
|
70 |
+
|
71 |
+
.lr-button {
|
72 |
+
background-color: #fff3ce;
|
73 |
+
}
|
74 |
+
|
75 |
+
.submit-button:hover {
|
76 |
+
background-color: #ffc83dc0;
|
77 |
+
}
|
78 |
+
|
79 |
+
.download-button {
|
80 |
+
background-color: #98ca56;
|
81 |
+
color: white;
|
82 |
+
font-weight: bold;
|
83 |
+
}
|
84 |
+
|
85 |
+
.download-button:hover {
|
86 |
+
background-color: #98ca56d1;
|
87 |
+
}
|
88 |
+
|
89 |
+
.output-title {
|
90 |
+
margin-top: 2rem;
|
91 |
+
margin-bottom: 0;
|
92 |
+
display: block;
|
93 |
+
background-color: #98ca56;
|
94 |
+
color: white;
|
95 |
+
font-weight: bold;
|
96 |
+
font-size: large;
|
97 |
+
padding: 6px 15px;
|
98 |
+
border-top-left-radius: 6px;
|
99 |
+
border-top-right-radius: 6px;
|
100 |
+
}
|
101 |
+
|
102 |
+
.output-box {
|
103 |
+
margin-top: 0;
|
104 |
+
padding: 6px 15px;
|
105 |
+
background-color: white;
|
106 |
+
border: 2px solid #98ca56;
|
107 |
+
border-bottom-left-radius: 6px;
|
108 |
+
border-bottom-right-radius: 6px;
|
109 |
+
}
|
110 |
+
</style>
|
111 |
+
</head>
|
112 |
+
|
113 |
+
<body>
|
114 |
+
<header>
|
115 |
+
<h1>🪞Mirror</h1>
|
116 |
+
<p>
|
117 |
+
🪞Mirror can help you deal with a wide range of Natural Language Understanding and Information Extraction tasks.
|
118 |
+
</p>
|
119 |
+
</header>
|
120 |
+
|
121 |
+
<main>
|
122 |
+
<div id="app">
|
123 |
+
<div>
|
124 |
+
<label for="instruction"><strong>Instruction</strong></label>
|
125 |
+
<input id="instruction" type="text" v-model="instruction" placeholder="Mirror mirror tell me ..." size="200">
|
126 |
+
</div>
|
127 |
+
<div>
|
128 |
+
<label for="schema"><strong>Schema Labels</strong></label>
|
129 |
+
<p>Split with <code>#</code> for multiple inputs</p>
|
130 |
+
<p>For entities, relations or classification, input <code>{"ent|rel|cls": ["cls1", "type2"]}</code> .</p>
|
131 |
+
<p>For events and hyper relations, input <code>{"type": ["role1", "role2"]}</code> .</p>
|
132 |
+
<input id="schema" type="text" v-model="schema" size="200">
|
133 |
+
<!-- <div>
|
134 |
+
<button @click.prevent="addCls">Class</button>
|
135 |
+
<button @click.prevent="addEnt">Entity</button>
|
136 |
+
<button @click.prevent="addDisconEnt">Discontinuous Entity</button>
|
137 |
+
<button @click.prevent="addRel">Relation</button>
|
138 |
+
<button @click.prevent="addEvent">Event Type</button>
|
139 |
+
<button @click.prevent="addHyperRel">Hyper Relation</button>
|
140 |
+
</div> -->
|
141 |
+
</div>
|
142 |
+
<div>
|
143 |
+
<label for="text"><strong>Text</strong></label>
|
144 |
+
<input id="text" type="text" v-model="text" size="200">
|
145 |
+
</div>
|
146 |
+
<!-- <div>
|
147 |
+
<label for="background"><strong>Background</strong></label>
|
148 |
+
<input id="background" type="text" v-model="background" size="200">
|
149 |
+
</div> -->
|
150 |
+
|
151 |
+
<div class="button-group">
|
152 |
+
<button @click.prevent="reset">Reset</button>
|
153 |
+
<button @click.prevent="clearOutput">Clear Output</button>
|
154 |
+
<button class="submit-button" @click.prevent="getResults">Ask Mirror</button>
|
155 |
+
</div>
|
156 |
+
|
157 |
+
<div v-if="timerHandler">
|
158 |
+
<p>⏱️ {{ searchSecondsString }}</p>
|
159 |
+
</div>
|
160 |
+
|
161 |
+
<div>
|
162 |
+
<div v-if="isNotEmptyObj(results)">
|
163 |
+
<label for="output"><strong>Output</strong></label>
|
164 |
+
<table>
|
165 |
+
<thead>
|
166 |
+
<th>Item</th>
|
167 |
+
<th>Predicted</th>
|
168 |
+
</thead>
|
169 |
+
<tbody>
|
170 |
+
<tr v-for="(value, key, index) in results" :key="index">
|
171 |
+
<template v-if="value.length">
|
172 |
+
<td>{{ key }}</td>
|
173 |
+
<td>{{ value }}</td>
|
174 |
+
</template>
|
175 |
+
</tr>
|
176 |
+
</tbody>
|
177 |
+
</table>
|
178 |
+
</div>
|
179 |
+
</div>
|
180 |
+
|
181 |
+
</div>
|
182 |
+
</main>
|
183 |
+
|
184 |
+
<footer>
|
185 |
+
<hr>
|
186 |
+
Made by Mirror Team w/ 💖
|
187 |
+
</footer>
|
188 |
+
|
189 |
+
<script type="module">
|
190 |
+
import { createApp, ref, computed, toRaw, watch } from 'vue'
|
191 |
+
|
192 |
+
createApp(
|
193 |
+
{
|
194 |
+
setup() {
|
195 |
+
const instruction = ref("")
|
196 |
+
const text = ref("")
|
197 |
+
const background = ref("")
|
198 |
+
const schema = ref("{}")
|
199 |
+
const results = ref({})
|
200 |
+
const timerHandler = ref(0)
|
201 |
+
const searchSeconds = ref(0.0)
|
202 |
+
const searchSecondsString = computed(() => {
|
203 |
+
return `${searchSeconds.value.toFixed(1)}s`
|
204 |
+
})
|
205 |
+
|
206 |
+
function isNotEmptyObj(obj) {
|
207 |
+
return Object.keys(obj).length > 0
|
208 |
+
}
|
209 |
+
|
210 |
+
function clearOutput() {
|
211 |
+
timerHandler.value = 0
|
212 |
+
results.value = {}
|
213 |
+
}
|
214 |
+
|
215 |
+
function reset() {
|
216 |
+
schema.value = "{}"
|
217 |
+
clearOutput()
|
218 |
+
}
|
219 |
+
|
220 |
+
function startTimer() {
|
221 |
+
searchSeconds.value = 0.0
|
222 |
+
timerHandler.value = setInterval(() => {
|
223 |
+
searchSeconds.value += 0.1
|
224 |
+
}, 100)
|
225 |
+
}
|
226 |
+
|
227 |
+
function endTimer() {
|
228 |
+
if (timerHandler.value > 0) {
|
229 |
+
clearInterval(timerHandler.value)
|
230 |
+
}
|
231 |
+
}
|
232 |
+
|
233 |
+
function getResults() {
|
234 |
+
clearOutput()
|
235 |
+
startTimer()
|
236 |
+
const data = {
|
237 |
+
"id": Date.now().toString(),
|
238 |
+
"instruction": instruction.value,
|
239 |
+
"schema": JSON.parse(schema.value),
|
240 |
+
"text": text.value,
|
241 |
+
"background": background.value,
|
242 |
+
"ans": {},
|
243 |
+
}
|
244 |
+
const postData = JSON.stringify({
|
245 |
+
"data": [data],
|
246 |
+
})
|
247 |
+
fetch(
|
248 |
+
"/process",
|
249 |
+
{
|
250 |
+
method: "POST",
|
251 |
+
headers: {
|
252 |
+
'Content-Type': 'application/json',
|
253 |
+
},
|
254 |
+
body: postData,
|
255 |
+
}
|
256 |
+
)
|
257 |
+
.then((response) => response.json())
|
258 |
+
.then((json) => {
|
259 |
+
if (json["ok"] === false) {
|
260 |
+
alert(json["msg"])
|
261 |
+
} else {
|
262 |
+
results.value = json["results"][0]["results"]
|
263 |
+
}
|
264 |
+
})
|
265 |
+
.catch((err) => { alert(err) })
|
266 |
+
.finally(() => endTimer())
|
267 |
+
}
|
268 |
+
|
269 |
+
return {
|
270 |
+
instruction,
|
271 |
+
text,
|
272 |
+
background,
|
273 |
+
schema,
|
274 |
+
results,
|
275 |
+
reset,
|
276 |
+
clearOutput,
|
277 |
+
getResults,
|
278 |
+
searchSecondsString,
|
279 |
+
timerHandler,
|
280 |
+
isNotEmptyObj,
|
281 |
+
}
|
282 |
+
}
|
283 |
+
}
|
284 |
+
).mount("#app")
|
285 |
+
</script>
|
286 |
+
</body>
|
287 |
+
|
288 |
+
</html>
|