.. _summarization-label: Summarization ============= Models ------ +-----------------------------------------------------------------------+-------+ | Model | Lang | +=======================================================================+=======+ | `mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization | EN | | `__ | | +-----------------------------------------------------------------------+-------+ | `nandakishormpai/t5-small-machine-articles-tag-generation | EN | | `__ | | +-----------------------------------------------------------------------+-------+ | `mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization | EN | | `__ | | +-----------------------------------------------------------------------+-------+ | `UrukHan/t5-russian-summarization | RU | | `__ | | +-----------------------------------------------------------------------+-------+ | `dmitry-vorobiev/rubert_ria_headlines | RU | | `__ | | +-----------------------------------------------------------------------+-------+ Datasets -------- 1. `ccdv/govreport-summarization `__ 1. **Lang**: EN 2. **Rows**: 973 3. **Preprocess**: 1. Select ``test`` split. 2. Rename column ``report`` to ``source``. 3. Rename column ``summary`` to ``target``. 4. Reset indexes. 2. `cnn_dailymail `__ 1. **Lang**: EN 2. **Rows**: 11490 3. **Preprocess**: 1. Select ``1.0.0`` subset. 2. Select ``test`` split. 3. Drop columns ``id``. 4. Rename column ``article`` to ``source``. 5. Rename column ``highlights`` to ``target``. 6. Delete duplicates in dataset. 7. Remove substring ``(CNN)`` for each ``source`` row. 8. Reset indexes. 3. `ccdv/pubmed-summarization `__ 1. **Lang**: EN 2. **Rows**: 6658 3. **Preprocess**: 1. Select ``test`` split. 2. Rename column ``article`` to ``source``. 3. Rename column ``abstract`` to ``target``. 4. Reset indexes. 4. `IlyaGusev/gazeta `__ 1. **Lang**: RU 2. **Rows**: 6793 3. **Preprocess**: 1. Select ``test`` split. 2. Drop columns ``title``, ``date``, ``url``. 3. Rename column ``text`` to ``source``. 4. Rename column ``summary`` to ``target``. 5. Reset indexes. 5. `d0rj/curation-corpus-ru `__ 1. **Lang**: RU 2. **Rows**: 30454 3. **Preprocess**: 1. Select ``train`` split. 2. Drop columns ``title``, ``date``, ``url``. 3. Rename column ``article_content`` to ``source``. 4. Rename column ``summary`` to ``target``. 5. Reset indexes. 6. `CarlBrendt/Summ_Dialog_News `__ 1. **Lang**: RU 2. **Rows**: 7609 3. **Preprocess**: 1. Select ``test`` split. 2. Rename column ``info`` to ``source``. 3. Rename column ``summary`` to ``target``. 4. Reset indexes. 7. `trixdade/reviews_russian `__ 1. **Lang**: RU 2. **Rows**: 95 3. **Preprocess**: 1. Select ``train`` split. 2. Rename column ``Reviews`` to ``source``. 3. Rename column ``Summary`` to ``target``. 4. Reset indexes. Supervised Fine-Tuning (SFT) Parameters --------------------------------------- .. note:: Set the parameter ``target_modules`` as ``["query", "key", "value", "dense"]`` for the `mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization `__, `mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization `__ and `dmitry-vorobiev/rubert_ria_headlines `__ models, and as ``["q", "k", "wi", "wo"]`` for the `UrukHan/t5-russian-summarization `__ model. .. note:: Set the parameters ``fine_tuning_steps=150, rank=24, alpha=36`` for the `mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization `__ as SFT parameters. In pair with `cnn_dailymail `__ dataset, set ``fine_tuning_steps=150, rank=24, alpha=48, learning_rate=1e-5`` Metrics ------- - BLEU - ROUGE .. note:: Use the ``rougeL`` metric and set ``seed=77`` parameter when loading the rouge metric.