Upload original BARECTB parser checkpoint, configuration, model card, and citation
Browse files- CITATION.bib +7 -0
- README.md +77 -0
- SHA256SUMS +1 -0
- barectb.model +3 -0
- barectb.model.yaml +60 -0
CITATION.bib
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@inproceedings{elmadani-etal-2026-barectb,
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title = {{BARECTB}: A Dependency Treebank and Parsing Benchmark for Arabic Children's Texts},
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author = {Elmadani, Khalid N. and Adel, Mohamed and AbuOdeh, Muhammed and Faraj, Reem and El-Gizuli, Jamila and Taha, Hanada and Habash, Nizar},
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booktitle = {Proceedings of ArabicNLP 2026},
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address = {Budapest, Hungary},
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year = {2026}
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}
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README.md
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---
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language:
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- ar
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base_model: CAMeL-Lab/bert-base-arabic-camelbert-msa
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tags:
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- dependency-parsing
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- arabic
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- catib
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- barectb
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- supar
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- pytorch
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---
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# CamelParser-BARECTB: BARECTB
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A supervised Arabic dependency parser using the CATiB representation, trained on **BARECTB** for **BARECTB: A Dependency Treebank and Parsing Benchmark for Arabic Children’s Texts** (ArabicNLP 2026).
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This repository contains the original paper-era `barectb.model` checkpoint. It is the same checkpoint distributed in the paper repository's `models/` directory. The later expanded 160K experiments use separate checkpoints.
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## Model
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- Encoder: [CAMeLBERT-MSA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa), as recorded in the checkpoint's training configuration.
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- Dependency parser: BERT-encoded biaffine parser implemented with [SuPar](https://github.com/yzhangcs/parser) and used through [CAMeL Parser](https://github.com/CAMeL-Lab/camel_parser).
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- Training condition: BARECTB.
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- Annotation: CATiB dependency relations.
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- Checkpoint format: native SuPar `.model`; load with CAMeL Parser/SuPar.
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The original `barectb.model.yaml` accompanies the checkpoint. Its historical training paths are preserved as provenance; inference uses the downloaded checkpoint.
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## Files
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| File | Description |
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| --- | --- |
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| `barectb.model` | Original trained parser checkpoint. |
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| `barectb.model.yaml` | Original training configuration. |
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| `SHA256SUMS` | Checkpoint SHA-256 checksum. |
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| `CITATION.bib` | Paper citation. |
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## Inference with CAMeL Parser
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Follow the installation instructions in the [CAMeL Parser main branch](https://github.com/CAMeL-Lab/camel_parser/tree/main), including its Python and CAMeL Tools data requirements. From that checkout, download this checkpoint into its `models/` directory:
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```python
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from huggingface_hub import hf_hub_download
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hf_hub_download(
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repo_id="CAMeL-Lab/camelparser-barectb-BARECTB",
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filename="barectb.model",
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local_dir="models",
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)
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```
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Then parse raw Arabic text:
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```bash
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python text_to_conll_cli.py -f text -m barectb.model -s "القطة نائمة."
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```
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Use `-i input.txt` for a file of sentences. The optional MSA-S31 morphology database requires the separate installation and access steps documented upstream.
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## Scope
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This checkpoint supports the paper's supervised Arabic dependency parsing experiments. Use the matching original BARECTB splits when reproducing that benchmark. Training corpora and morphology resources are separate from this model repository.
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## Citation
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Elmadani, Khalid N., Mohamed Adel, Muhammed AbuOdeh, Reem Faraj, Jamila El-Gizuli, Hanada Taha and Nizar Habash. BARECTB: A Dependency Treebank and Parsing Benchmark for Arabic Children’s Texts. In Proceedings of ArabicNLP 2026, Budapest, Hungary, 2026.
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```bibtex
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@inproceedings{elmadani-etal-2026-barectb,
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title = {{BARECTB}: A Dependency Treebank and Parsing Benchmark for Arabic Children's Texts},
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author = {Elmadani, Khalid N. and Adel, Mohamed and AbuOdeh, Muhammed and Faraj, Reem and El-Gizuli, Jamila and Taha, Hanada and Habash, Nizar},
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booktitle = {Proceedings of ArabicNLP 2026},
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address = {Budapest, Hungary},
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year = {2026}
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}
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```
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SHA256SUMS
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ad6084fea414743b0df1b96c3c9d65fca91da4df98f697d7ef183749a8d705b8 barectb.model
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barectb.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:ad6084fea414743b0df1b96c3c9d65fca91da4df98f697d7ef183749a8d705b8
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size 445276633
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barectb.model.yaml
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amp: false
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batch_size: 5000
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bert: CAMeL-Lab/bert-base-arabic-camelbert-msa
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bert_pad_index: null
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bert_pooling: mean
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binarize: false
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bos_index: 2
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buckets: 32
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build: false
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cache: false
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char_pad_index: null
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checkpoint: false
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clip: 5.0
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dev: /scratch/ma10074/barectb/experiments/dev_barectb.conllx
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device: '0'
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dist: ddp
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embed: glove-6b-100
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encoder: bert
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encoder_dropout: 0.1
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epochs: 10
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eps: 1.0e-08
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even: false
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feat: null
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fix_len: 20
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local_rank: 0
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lr: 5.0e-05
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lr_rate: 10
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max_len: null
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min_freq: 2
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mix_dropout: 0.0
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mlp_dropout: 0.33
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mode: train
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mu: 0.9
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n_arc_mlp: 500
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n_bert_layers: 4
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n_chars: null
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n_rel_mlp: 100
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n_rels: 9
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n_tags: null
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n_words: 30000
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nu: 0.999
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pad_index: 0
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partial: false
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path: /scratch/ma10074/barectb/models/barectb.model
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patience: 100
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proj: true
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punct: false
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seed: 1
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steps: 160
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test: /scratch/ma10074/barectb/experiments/test_barectb.conllx
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threads: 16
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train: /scratch/ma10074/barectb/experiments/train_barectb.conllx
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tree: true
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unk_index: 1
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update_steps: 4
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verbose: true
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wandb: false
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warmup: 0.1
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weight_decay: 0
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workers: 0
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