| """Canonical model, checkpoint-selection, and Hugging Face repository registry.""" |
|
|
| from __future__ import annotations |
|
|
| from pathlib import Path |
| from typing import Any |
|
|
|
|
| NAMESPACE = "nishan-chatterjee" |
| COLLECTION_SLUG = ( |
| "nishan-chatterjee/aspect-based-sentiment-analysis-6a9016a6d9cab7b093f122d3" |
| ) |
| TOOLKIT_REPO = f"{NAMESPACE}/aspect-based-sentiment-analysis" |
| LANGUAGES = ("hbs", "slovenian") |
| MODES = ("masked", "unmasked") |
|
|
|
|
| MODEL_SPECS: dict[str, dict[str, Any]] = { |
| "xlmr": { |
| "display_name": "XLM-R", |
| "backend": "encoder", |
| "base_model": "FacebookAI/xlm-roberta-base", |
| "local_base_dir": "xlm-roberta-base", |
| "max_length": 512, |
| "hf_repo": f"{NAMESPACE}/aspectbench-xlmr", |
| }, |
| "han-xlmr": { |
| "display_name": "HAN-XLM-R", |
| "backend": "han", |
| "base_model": "FacebookAI/xlm-roberta-base", |
| "local_base_dir": "xlm-roberta-base", |
| "max_length": 96, |
| "max_sentences": 128, |
| "hf_repo": f"{NAMESPACE}/aspectbench-han-xlmr", |
| }, |
| "longformer": { |
| "display_name": "XLM-R Longformer", |
| "backend": "encoder", |
| "base_model": "markussagen/xlm-roberta-longformer-base-4096", |
| "local_base_dir": "markussagen_xlm-roberta-longformer-base-4096", |
| "max_length": 4096, |
| "global_attention": True, |
| "hf_repo": f"{NAMESPACE}/aspectbench-longformer", |
| }, |
| "mdeberta-v3": { |
| "display_name": "mDeBERTa-v3", |
| "backend": "encoder", |
| "base_model": "microsoft/mdeberta-v3-base", |
| "local_base_dir": "microsoft_mdeberta-v3-base", |
| "max_length": 512, |
| "hf_repo": f"{NAMESPACE}/aspectbench-mdeberta-v3", |
| }, |
| "mt5": { |
| "display_name": "mT5", |
| "backend": "mt5", |
| "base_model": "google/mt5-base", |
| "local_base_dir": "google_mt5-base", |
| "max_length": 512, |
| "max_target_length": 8, |
| "hf_repo": f"{NAMESPACE}/aspectbench-mt5", |
| }, |
| "slavic-specific": { |
| "display_name": "BERTić / SloBERTa", |
| "backend": "encoder", |
| "base_model": { |
| "hbs": "classla/bcms-bertic", |
| "slovenian": "EMBEDDIA/sloberta", |
| }, |
| "local_base_dir": { |
| "hbs": "classla_bcms-bertic", |
| "slovenian": "EMBEDDIA_sloberta", |
| }, |
| "max_length": 512, |
| "hf_repo": f"{NAMESPACE}/aspectbench-slavic-specific", |
| }, |
| "bge-m3-mlp": { |
| "display_name": "BGE-M3 dense + MLP", |
| "backend": "bge", |
| "base_model": "BAAI/bge-m3", |
| "local_base_dir": "embeddings/bge-m3", |
| "max_length": 8192, |
| "hf_repo": f"{NAMESPACE}/aspectbench-bge-m3-mlp", |
| }, |
| } |
|
|
|
|
| def _entry( |
| source: str | None, |
| run: int | None, |
| validation_macro_f1: float | None, |
| *, |
| reason: str | None = None, |
| expected_source: str | None = None, |
| ) -> dict[str, Any]: |
| return { |
| "source": source, |
| "run": run, |
| "validation_macro_f1": validation_macro_f1, |
| "available": source is not None, |
| "unavailable_reason": reason, |
| "expected_source": expected_source, |
| } |
|
|
|
|
| CHECKPOINTS: dict[tuple[str, str, str], dict[str, Any]] = { |
| ("xlmr", "hbs", "masked"): _entry( |
| "additional-tasks/xlmr_truncated/masked/serbian/best_model_0.pt", |
| 0, |
| 0.9247234996073129, |
| ), |
| ("xlmr", "slovenian", "masked"): _entry( |
| "additional-tasks/xlmr_truncated/masked/slovenian/best_model_2.pt", |
| 2, |
| 0.8357596148205779, |
| ), |
| ("xlmr", "hbs", "unmasked"): _entry( |
| None, |
| 1, |
| 0.9261041473729551, |
| reason=( |
| "Validation metrics identify the best unmasked run, but its trained " |
| "checkpoint file is absent from the source tree. Retraining or archive " |
| "recovery is required." |
| ), |
| expected_source="models/xlmr/no_summary/serbian/best_model_1.pt", |
| ), |
| ("xlmr", "slovenian", "unmasked"): _entry( |
| None, |
| 2, |
| 0.8286127750538895, |
| reason=( |
| "Validation metrics identify the best unmasked run, but its trained " |
| "checkpoint file is absent from the source tree. Retraining or archive " |
| "recovery is required." |
| ), |
| expected_source="models/xlmr/no_summary/slovenian/best_model_2.pt", |
| ), |
| ("han-xlmr", "hbs", "masked"): _entry( |
| "results/global-context-modelling/simplified-dart-xlmr/serbian/best_model_2.pt", |
| 2, |
| 0.9137775530809181, |
| ), |
| ("han-xlmr", "slovenian", "masked"): _entry( |
| "results/global-context-modelling/simplified-dart-xlmr/slovenian/best_model_1.pt", |
| 1, |
| 0.8108233024053296, |
| ), |
| ("han-xlmr", "hbs", "unmasked"): _entry( |
| None, |
| 2, |
| 0.9106720097631231, |
| reason=( |
| "Validation metrics identify the best aspect-marker run, but its trained " |
| "checkpoint file is absent from the source tree. Retraining or archive " |
| "recovery is required." |
| ), |
| expected_source=( |
| "models/global-context-modelling/with-aspect-markers/serbian/best_model_2.pt" |
| ), |
| ), |
| ("han-xlmr", "slovenian", "unmasked"): _entry( |
| None, |
| 2, |
| 0.8127192586145947, |
| reason=( |
| "Validation metrics identify the best aspect-marker run, but its trained " |
| "checkpoint file is absent from the source tree. Retraining or archive " |
| "recovery is required." |
| ), |
| expected_source=( |
| "models/global-context-modelling/with-aspect-markers/slovenian/best_model_2.pt" |
| ), |
| ), |
| ("longformer", "hbs", "masked"): _entry( |
| "reviews/longformer/masked/serbian/best_model_0.pt", 0, 0.9235562204487023 |
| ), |
| ("longformer", "slovenian", "masked"): _entry( |
| "reviews/longformer/masked/slovenian/best_model_1.pt", 1, 0.8349811751435684 |
| ), |
| ("longformer", "hbs", "unmasked"): _entry( |
| "reviews/longformer/unmasked/serbian/best_model_0.pt", 0, 0.9237049934972151 |
| ), |
| ("longformer", "slovenian", "unmasked"): _entry( |
| "reviews/longformer/unmasked/slovenian/best_model_1.pt", 1, 0.8250958292470165 |
| ), |
| ("mdeberta-v3", "hbs", "masked"): _entry( |
| "reviews/mdeberta/masked/serbian/best_model_0.pt", 0, 0.9150760776163819 |
| ), |
| ("mdeberta-v3", "slovenian", "masked"): _entry( |
| "reviews/mdeberta/masked/slovenian/best_model_1.pt", 1, 0.8242447008523016 |
| ), |
| ("mdeberta-v3", "hbs", "unmasked"): _entry( |
| "reviews/mdeberta/unmasked/serbian/best_model_0.pt", 0, 0.9190600266461267 |
| ), |
| ("mdeberta-v3", "slovenian", "unmasked"): _entry( |
| "reviews/mdeberta/unmasked/slovenian/best_model_1.pt", 1, 0.8223988954252537 |
| ), |
| ("mt5", "hbs", "masked"): _entry( |
| "reviews/mt5/masked/serbian/best_model_0.pt", 0, 0.889948707182005 |
| ), |
| ("mt5", "slovenian", "masked"): _entry( |
| "reviews/mt5/masked/slovenian/best_model_1.pt", 1, 0.8012255203557931 |
| ), |
| ("mt5", "hbs", "unmasked"): _entry( |
| "reviews/mt5/unmasked/serbian/best_model_1.pt", 1, 0.8942548569348862 |
| ), |
| ("mt5", "slovenian", "unmasked"): _entry( |
| "reviews/mt5/unmasked/slovenian/best_model_2.pt", 2, 0.8070351391836906 |
| ), |
| ("slavic-specific", "hbs", "masked"): _entry( |
| "reviews/slavic_specific/masked/serbian/best_model_1.pt", 1, 0.9151353276491324 |
| ), |
| ("slavic-specific", "slovenian", "masked"): _entry( |
| "reviews/slavic_specific/masked/slovenian/best_model_2.pt", 2, 0.8545257213567837 |
| ), |
| ("slavic-specific", "hbs", "unmasked"): _entry( |
| "reviews/slavic_specific/unmasked/serbian/best_model_0.pt", 0, 0.9250658853407349 |
| ), |
| ("slavic-specific", "slovenian", "unmasked"): _entry( |
| "reviews/slavic_specific/unmasked/slovenian/best_model_2.pt", 2, 0.8638678818708625 |
| ), |
| ("bge-m3-mlp", "hbs", "masked"): _entry( |
| None, |
| 2, |
| 0.8840815245920188, |
| reason="Validation metrics exist, but the selected trained dense MLP head file is absent.", |
| expected_source="models/bge-m3_mlp/masked/serbian/best_model_2.pt", |
| ), |
| ("bge-m3-mlp", "slovenian", "masked"): _entry( |
| None, |
| 1, |
| 0.7514188081139693, |
| reason="Validation metrics exist, but the selected trained dense MLP head file is absent.", |
| expected_source="models/bge-m3_mlp/masked/slovenian/best_model_1.pt", |
| ), |
| ("bge-m3-mlp", "hbs", "unmasked"): _entry( |
| None, |
| 1, |
| 0.8894579185247774, |
| reason="Validation metrics exist, but the selected trained dense MLP head file is absent.", |
| expected_source="models/bge-m3_mlp/whole/serbian/best_model_1.pt", |
| ), |
| ("bge-m3-mlp", "slovenian", "unmasked"): _entry( |
| None, |
| 1, |
| 0.7393257242124599, |
| reason="Validation metrics exist, but the selected trained dense MLP head file is absent.", |
| expected_source="models/bge-m3_mlp/whole/slovenian/best_model_1.pt", |
| ), |
| } |
|
|
|
|
| def _apply_local_release_metadata() -> None: |
| """Expose newly retrained slots before their metadata reaches the remote.""" |
|
|
| models_root = Path(__file__).resolve().parents[1] / "models" |
| for model_name in MODEL_SPECS: |
| path = models_root / model_name / "availability.json" |
| if not path.is_file(): |
| continue |
| try: |
| import json |
|
|
| entries = json.loads(path.read_text(encoding="utf-8"))["entries"] |
| except (KeyError, OSError, TypeError, ValueError): |
| continue |
| for entry in entries: |
| key = (model_name, entry.get("language"), entry.get("mode")) |
| weight = models_root / model_name / str(entry.get("weight_path", "")).split( |
| f"{model_name}/", 1 |
| )[-1] |
| if key not in CHECKPOINTS or not entry.get("available") or not weight.is_file(): |
| continue |
| CHECKPOINTS[key].update( |
| available=True, |
| unavailable_reason=None, |
| validation_macro_f1=entry.get("validation_macro_f1"), |
| run=entry.get("selected_split", CHECKPOINTS[key].get("run")), |
| ) |
|
|
|
|
| _apply_local_release_metadata() |
|
|
|
|
| def model_spec(model_name: str, language: str) -> dict[str, Any]: |
| spec = dict(MODEL_SPECS[model_name]) |
| for key in ("base_model", "local_base_dir"): |
| if isinstance(spec[key], dict): |
| spec[key] = spec[key][language] |
| return spec |
|
|
|
|
| def weight_path(model_root: str | Path, model_name: str, language: str, mode: str) -> Path: |
| return Path(model_root) / model_name / language / f"{mode}.pt" |
|
|
|
|
| def all_slots(): |
| for model_name in MODEL_SPECS: |
| for language in LANGUAGES: |
| for mode in MODES: |
| yield model_name, language, mode, CHECKPOINTS[(model_name, language, mode)] |
|
|
