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lmqg
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bart-large-squad-qg

Text2Text Generation
Transformers
PyTorch
English
bart
question generation
Eval Results
Inference Endpoints
Model card Files Community
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@@ -65,6 +65,9 @@ All evaluations were done using our [evaluation script](https://github.com/asahi
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  | 26.16 | 53.84 | 27.07 | 91.00 | 64.99 |
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  ## Fine-tuning Parameters
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  We ran grid search to find the best hyper-parameters and continued fine-tuning until the validation metric decrease.
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  The best hyper-parameters can be found [here](https://huggingface.co/asahi417/lmqg-bart-large-squad/raw/main/trainer_config.json), and fine-tuning script is released in [our repository](https://github.com/asahi417/lm-question-generation).
 
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  | ------ | -------- | ------ | --------- | ---------- |
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  | 26.16 | 53.84 | 27.07 | 91.00 | 64.99 |
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+ - [metric file](https://huggingface.co/asahi417/lmqg-bart-large-squad/raw/main/eval/metric.first.sentence.paragraph_answer.question.asahi417_qg_squad.default.json)
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  ## Fine-tuning Parameters
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  We ran grid search to find the best hyper-parameters and continued fine-tuning until the validation metric decrease.
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  The best hyper-parameters can be found [here](https://huggingface.co/asahi417/lmqg-bart-large-squad/raw/main/trainer_config.json), and fine-tuning script is released in [our repository](https://github.com/asahi417/lm-question-generation).