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--- |
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license: cc-by-4.0 |
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metrics: |
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- bleu4 |
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- meteor |
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- rouge-l |
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- bertscore |
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- moverscore |
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language: it |
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datasets: |
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- lmqg/qg_itquad |
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pipeline_tag: text2text-generation |
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tags: |
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- question generation |
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widget: |
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- text: "<hl> Dopo il 1971 <hl> , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento." |
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example_title: "Question Generation Example 1" |
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- text: "L' individuazione del petrolio e lo sviluppo di nuovi giacimenti richiedeva in genere <hl> da cinque a dieci anni <hl> prima di una produzione significativa." |
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example_title: "Question Generation Example 2" |
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- text: "il <hl> Giappone <hl> è stato il paese più dipendente dal petrolio arabo." |
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example_title: "Question Generation Example 3" |
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model-index: |
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- name: lmqg/mt5-base-itquad |
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results: |
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- task: |
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name: Text2text Generation |
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type: text2text-generation |
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dataset: |
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name: lmqg/qg_itquad |
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type: default |
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args: default |
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metrics: |
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- name: BLEU4 |
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type: bleu4 |
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value: 0.07701528877424803 |
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- name: ROUGE-L |
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type: rouge-l |
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value: 0.22511430414292052 |
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- name: METEOR |
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type: meteor |
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value: 0.17997929735967222 |
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- name: BERTScore |
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type: bertscore |
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value: 0.8116317604756539 |
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- name: MoverScore |
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type: moverscore |
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value: 0.5711254911196173 |
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--- |
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# Language Models Fine-tuning on Question Generation: `lmqg/mt5-base-itquad` |
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This model is fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) for question generation task on the |
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[lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default). |
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### Overview |
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- **Language model:** [google/mt5-base](https://huggingface.co/google/mt5-base) |
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- **Language:** it |
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- **Training data:** [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (default) |
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- **Online Demo:** [https://autoqg.net/](https://autoqg.net/) |
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- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation) |
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- **Paper:** [TBA](TBA) |
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### Usage |
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```python |
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from transformers import pipeline |
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model_path = 'lmqg/mt5-base-itquad' |
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pipe = pipeline("text2text-generation", model_path) |
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# Question Generation |
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question = pipe('<hl> Dopo il 1971 <hl> , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento.') |
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``` |
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## Evaluation Metrics |
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### Metrics |
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| Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link | |
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|:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:| |
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| [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) | default | 0.077 | 0.225 | 0.18 | 0.812 | 0.571 | [link](https://huggingface.co/lmqg/mt5-base-itquad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json) | |
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## Training hyperparameters |
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The following hyperparameters were used during fine-tuning: |
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- dataset_path: lmqg/qg_itquad |
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- dataset_name: default |
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- input_types: ['paragraph_answer'] |
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- output_types: ['question'] |
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- prefix_types: None |
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- model: google/mt5-base |
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- max_length: 512 |
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- max_length_output: 32 |
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- epoch: 11 |
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- batch: 4 |
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- lr: 0.001 |
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- fp16: False |
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- random_seed: 1 |
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- gradient_accumulation_steps: 16 |
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- label_smoothing: 0.15 |
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The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/mt5-base-itquad/raw/main/trainer_config.json). |
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## Citation |
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TBA |
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