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model update

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  1. README.md +34 -3
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@@ -48,11 +48,29 @@ model-index:
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  value: 0.6341318883185333
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  ---
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- # Language Models Fine-tuning on Question Generation: `lmqg/t5-large-subjqa-grocery`
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  This model is fine-tuned version of [lmqg/t5-large-squad](https://huggingface.co/lmqg/t5-large-squad) for question generation task on the
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- [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) (dataset_name: grocery).
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  This model is continuously fine-tuned with [lmqg/t5-large-squad](https://huggingface.co/lmqg/t5-large-squad).
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  ### Overview
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  - **Language model:** [lmqg/t5-large-squad](https://huggingface.co/lmqg/t5-large-squad)
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  - **Language:** en
@@ -71,6 +89,7 @@ pipe = pipeline("text2text-generation", model_path)
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  # Question Generation
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  question = pipe('generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
 
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  ```
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  ## Evaluation Metrics
@@ -107,4 +126,16 @@ The following hyperparameters were used during fine-tuning:
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  The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/t5-large-subjqa-grocery/raw/main/trainer_config.json).
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  ## Citation
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- TBA
 
 
 
 
 
 
 
 
 
 
 
 
 
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  value: 0.6341318883185333
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  ---
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+ # Model Card of `lmqg/t5-large-subjqa-grocery`
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  This model is fine-tuned version of [lmqg/t5-large-squad](https://huggingface.co/lmqg/t5-large-squad) for question generation task on the
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+ [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) (dataset_name: grocery) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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  This model is continuously fine-tuned with [lmqg/t5-large-squad](https://huggingface.co/lmqg/t5-large-squad).
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+ Please cite our paper if you use the model ([TBA](TBA)).
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+
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+ ```
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+
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+ @inproceedings{ushio-etal-2022-generative,
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+ title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration: {A} {U}nified {B}enchmark and {E}valuation",
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+ author = "Ushio, Asahi and
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+ Alva-Manchego, Fernando and
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+ Camacho-Collados, Jose",
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+ booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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+ month = dec,
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+ year = "2022",
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+ address = "Abu Dhabi, U.A.E.",
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+ publisher = "Association for Computational Linguistics",
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+ }
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+
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+ ```
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+
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  ### Overview
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  - **Language model:** [lmqg/t5-large-squad](https://huggingface.co/lmqg/t5-large-squad)
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  - **Language:** en
 
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  # Question Generation
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  question = pipe('generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
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+
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  ```
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  ## Evaluation Metrics
 
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  The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/t5-large-subjqa-grocery/raw/main/trainer_config.json).
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  ## Citation
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+
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+ @inproceedings{ushio-etal-2022-generative,
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+ title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration: {A} {U}nified {B}enchmark and {E}valuation",
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+ author = "Ushio, Asahi and
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+ Alva-Manchego, Fernando and
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+ Camacho-Collados, Jose",
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+ booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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+ month = dec,
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+ year = "2022",
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+ address = "Abu Dhabi, U.A.E.",
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+ publisher = "Association for Computational Linguistics",
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+ }
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+