{"id":25639774,"url":"https://github.com/sweep76/conditional-random-field","last_synced_at":"2025-08-17T12:36:32.558Z","repository":{"id":275079299,"uuid":"925003288","full_name":"Sweep76/Conditional-Random-Field","owner":"Sweep76","description":"CRF for sequence labeling tasks. 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It includes methods for training the model using stochastic gradient descent, making predictions, and evaluating performance on training and development datasets.\n\n# Conditional Random Field\n\n## Structure\n\n```sh\n.\n├── bigdata\n│   ├── dev.conll\n│   ├── test.conll\n│   └── train.conll\n├── data\n│   ├── dev.conll\n│   └── train.conll\n├── results\n│   ├── acrf.txt\n│   ├── bacrf.txt\n│   ├── bcrf.txt\n│   ├── boacrf.txt\n│   ├── bocrf.txt\n│   ├── crf.txt\n│   ├── oacrf.txt\n│   └── ocrf.txt\n├── config.py\n├── crf.py\n├── ocrf.py\n├── README.md\n└── run.py\n```\n\n## Usage\n\n```sh\n$ python run.py -h\nusage: run.py [-h] [--bigdata] [--anneal] [--optimize] [--regularize]\n              [--seed SEED] [--file FILE]\n\nCreate Conditional Random Field(CRF) for POS Tagging.\n\noptional arguments:\n  -h, --help            show this help message and exit\n  --bigdata, -b         use big data\n  --anneal, -a          use simulated annealing\n  --optimize, -o        use feature extracion optimization\n  --regularize, -r      use L2 regularization\n  --seed SEED, -s SEED  set the seed for generating random numbers\n  --file FILE, -f FILE  set where to store the model\n# e.g. Feature extraction optimization + simulated annealing\n$ python run.py -b --optimize --anneal\n```\n\n## Results\n\n| Large Dataset | Feature Extraction Optimization | Simulated Annealing | Iterations |  dev/P   |  test/P  |     mT(s)      |\n| :-----------: | :---------------------------: | :----------------: | :--------: | :------: | :------: | :------------: |\n|      ×       |              ×                |         ×         |   12/18    | 88.6405% |    *     | 0:00:52.687575 |\n|      ×       |              ×                |         √         |   10/16    | 88.6504% |    *     | 0:00:52.967660 |\n|      ×       |              √                |         ×         |   10/16    | 88.9425% |    *     | 0:00:16.543064 |\n|      ×       |              √                |         √         |   12/18    | 88.9247% |    *     | 0:00:17.004330 |\n|      √       |              ×                |         ×         |   14/25    | 93.8587% | 93.7054% | 0:57:13.132850 |\n|      √       |              ×                |         √         |   37/48    | 94.2190% | 93.9665% | 0:56:30.033807 |\n|      √       |              √                |         ×         |   15/26    | 93.9705% | 93.8537% | 0:13:33.869449 |\n|      √       |              √                |         √         |   13/24    | 94.2107% | 94.0425% | 0:13:25.669687 |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsweep76%2Fconditional-random-field","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsweep76%2Fconditional-random-field","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsweep76%2Fconditional-random-field/lists"}