--- license: cc-by-4.0 metrics: - bleu4 - meteor - rouge-l - bertscore - moverscore language: en datasets: - lmqg/qg_squad pipeline_tag: text2text-generation tags: - question generation widget: - text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records." example_title: "Question Generation Example 1" - text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records." example_title: "Question Generation Example 2" - text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records ." example_title: "Question Generation Example 3" model-index: - name: lmqg/t5-small-squad-default results: - task: name: Text2text Generation type: text2text-generation dataset: name: lmqg/qg_squad type: default args: default metrics: - name: BLEU4 type: bleu4 value: 0.2266718077651334 - name: ROUGE-L type: rouge-l value: 0.4953920093132268 - name: METEOR type: meteor value: 0.24675728793398077 - name: BERTScore type: bertscore value: 0.9016671782685416 - name: MoverScore type: moverscore value: 0.630633217445346 --- # Language Models Fine-tuning on Question Generation: `lmqg/t5-small-squad-default` This model is fine-tuned version of [t5-small](https://huggingface.co/t5-small) for question generation task on the [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (dataset_name: default). This model is fine-tuned without parameter search (default configuration is taken from [ERNIE-GEN](https://arxiv.org/abs/2001.11314)). ### Overview - **Language model:** [t5-small](https://huggingface.co/t5-small) - **Language:** en - **Training data:** [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (default) - **Online Demo:** [https://autoqg.net/](https://autoqg.net/) - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation) - **Paper:** [TBA](TBA) ### Usage ```python from transformers import pipeline model_path = 'lmqg/t5-small-squad-default' pipe = pipeline("text2text-generation", model_path) # Question Generation input_text = 'generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.' question = pipe(input_text) ``` ## Evaluation Metrics ### Metrics | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link | |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:| | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.2266718077651334 | 0.4953920093132268 | 0.24675728793398077 | 0.9016671782685416 | 0.630633217445346 | [link](https://huggingface.co/lmqg/t5-small-squad-default/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) | ## Training hyperparameters The following hyperparameters were used during fine-tuning: - dataset_path: lmqg/qg_squad - dataset_name: default - input_types: ['paragraph_answer'] - output_types: ['question'] - prefix_types: ['qg'] - model: t5-small - max_length: 512 - max_length_output: 32 - epoch: 10 - batch: 32 - lr: 1.25e-05 - fp16: False - random_seed: 1 - gradient_accumulation_steps: 1 - label_smoothing: 0.1 The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/t5-small-squad-default/raw/main/trainer_config.json). ## Citation TBA