diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..a6344aac8c09253b3b630fb776ae94478aa0275b --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d2dec62e71f054ef2b71bb1e6b5345e19c6efe19 --- /dev/null +++ b/README.md @@ -0,0 +1,81 @@ +--- +license: apache-2.0 +language: +- ar +tags: +- text-classification +- arabic +- ensemble +- doha-ai-challenge +--- + +# Doha AI Challenge — fine-tuned checkpoints (Team Salahh) + +This repository holds the **fine-tuned model checkpoints** for our winning solution to the +**Google Cloud Doha AI Challenge** (6-target Arabic-news classification, weighted-F1). + +The solution is an ensemble of Arabic transformer classifiers built on **9 pretrained backbones**, +each fine-tuned under several configurations/seeds. Every run is trained with 5-fold cross-validation, +so each of the 42 runs contributes **5 fold checkpoints**: + +``` +/fold0.pt fold1.pt fold2.pt fold3.pt fold4.pt # 42 tags x 5 folds = 210 checkpoints +``` + +Each `fold*.pt` is a `state_dict` (bf16) of a multi-task model: a shared encoder + 6 linear +classification heads (one per target). ~92 GB total. + +These checkpoints are consumed by the **`solution/`** code of the competition submission package +(`infer.py` / `reproduce_from_checkpoints.ipynb`), together with `recipe.json` (per-target model sets) +and `weights.json` (ensemble weights), to reproduce the final `clean.csv`. + +--- + +## 1. Download the checkpoints + +```bash +pip install -U "huggingface_hub[cli]" + +# into the solution/ folder of the submission package, as checkpoints//fold*.pt +huggingface-cli download salahh297/doha-checkpoints \ + --repo-type model --local-dir solution/checkpoints +``` +(Or in Python:) +```python +from huggingface_hub import snapshot_download +snapshot_download("salahh297/doha-checkpoints", repo_type="model", + local_dir="solution/checkpoints") +``` + +After download, the layout is `solution/checkpoints//fold{0..4}.pt`. + +--- + +## 2. Reproduce `clean.csv` from the checkpoints (GPU) + +You need the competition **`solution/`** folder (code + `recipe.json` + `weights.json` + +`data/Train.csv`, `data/Test.csv`) alongside the downloaded `checkpoints/`. + +```bash +cd solution +pip install torch "transformers==4.57.1" accelerate sentencepiece arabert farasapy scikit-learn pandas numpy + +# script: +python3 infer.py +# or the notebook (same result): +# jupyter nbconvert --to notebook --execute reproduce_from_checkpoints.ipynb +``` + +`infer.py` rebuilds each model, loads its five fold checkpoints from `checkpoints//fold*.pt`, +runs them forward on the test set (GPU), averages the five test-probability sets per model, and +combines the per-target model sets (`recipe.json`) with the ensemble weights (`weights.json`) to +write `clean.csv`. + +- **GPU:** A100 40GB, or A100 / H100 80GB (H100 80GB recommended). +- The farasa-segmented run preprocesses the test text with the farasa segmenter and is slow + (tens of minutes); all other runs are fast. +- Fixed seeds are used throughout, so the pipeline is reproducible. + +--- + +_Team: Salahh._ diff --git a/arabertL/fold0.pt b/arabertL/fold0.pt new file mode 100644 index 0000000000000000000000000000000000000000..6ae867ed7f84734bae5635dcb275fade4b55cb5e --- /dev/null +++ b/arabertL/fold0.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b930d0d7af1ddd539f7351a88403106a78d7b924a51c1d61df91533df3386594 +size 739017447 diff --git a/arabertL/fold1.pt b/arabertL/fold1.pt new file mode 100644 index 0000000000000000000000000000000000000000..80212f94408dcfe328fd2500e76b47ab06e6dc09 --- /dev/null +++ b/arabertL/fold1.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9034272bb154f7272ca52bd6c3019a13d108473785a62762d7d9addb12a04cfa +size 739017447 diff --git a/arabertL/fold2.pt b/arabertL/fold2.pt new file mode 100644 index 0000000000000000000000000000000000000000..9f04bece35c19ac13f6fde109ffb576daed2ecdd --- /dev/null +++ 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