model update
Browse files
README.md
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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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value: 57.11
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---
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# Model Card of `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 [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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from lmqg import TransformersQG
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# initialize model
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model = TransformersQG(language="it", model="lmqg/mt5-base-itquad")
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# model prediction
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questions = model.generate_q(list_context="Dopo il 1971 , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento.", list_answer="Dopo il 1971")
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```python
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from transformers import pipeline
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pipe = pipeline("text2text-generation", "lmqg/mt5-base-itquad")
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output = 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
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- ***Metric (Question Generation)***: [raw metric file](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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| | Score | Type | Dataset |
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|:-----------|--------:|:--------|:-----------------------------------------------------------------|
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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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```
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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-qg
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results:
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- task:
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name: Text2text Generation
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value: 57.11
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---
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# Model Card of `lmqg/mt5-base-itquad-qg`
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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 [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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from lmqg import TransformersQG
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# initialize model
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model = TransformersQG(language="it", model="lmqg/mt5-base-itquad-qg")
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# model prediction
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questions = model.generate_q(list_context="Dopo il 1971 , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento.", list_answer="Dopo il 1971")
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```python
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from transformers import pipeline
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pipe = pipeline("text2text-generation", "lmqg/mt5-base-itquad-qg")
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output = 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
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- ***Metric (Question Generation)***: [raw metric file](https://huggingface.co/lmqg/mt5-base-itquad-qg/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_itquad.default.json)
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| | Score | Type | Dataset |
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|:-----------|--------:|:--------|:-----------------------------------------------------------------|
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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-qg/raw/main/trainer_config.json).
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## Citation
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```
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