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README.md

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+
+---
+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: "<hl> Beyonce <hl> 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: "Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
+  example_title: "Question Generation Example 2" 
+- text: "Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic,  <hl> Cadillac Records <hl> ."
+  example_title: "Question Generation Example 3" 
+model-index:
+- name: vocabtrimmer/mt5-small-trimmed-en-5000-squad-qg
+  results:
+  - task:
+      name: Text2text Generation
+      type: text2text-generation
+    dataset:
+      name: lmqg/qg_squad
+      type: default
+      args: default
+    metrics:
+    - name: BLEU4 (Question Generation)
+      type: bleu4_question_generation
+      value: 22.84
+    - name: ROUGE-L (Question Generation)
+      type: rouge_l_question_generation
+      value: 50.34
+    - name: METEOR (Question Generation)
+      type: meteor_question_generation
+      value: 24.75
+    - name: BERTScore (Question Generation)
+      type: bertscore_question_generation
+      value: 90.01
+    - name: MoverScore (Question Generation)
+      type: moverscore_question_generation
+      value: 63.43
+---
+
+# Model Card of `vocabtrimmer/mt5-small-trimmed-en-5000-squad-qg`
+This model is fine-tuned version of [ckpts/mt5-small-trimmed-en-5000](https://huggingface.co/ckpts/mt5-small-trimmed-en-5000) for question generation task on the [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
+
+
+### Overview
+- **Language model:** [ckpts/mt5-small-trimmed-en-5000](https://huggingface.co/ckpts/mt5-small-trimmed-en-5000)   
+- **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:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
+
+### Usage
+- With [`lmqg`](https://github.com/asahi417/lm-question-generation#lmqg-language-model-for-question-generation-)
+```python
+from lmqg import TransformersQG
+
+# initialize model
+model = TransformersQG(language="en", model="vocabtrimmer/mt5-small-trimmed-en-5000-squad-qg")
+
+# model prediction
+questions = model.generate_q(list_context="William Turner was an English painter who specialised in watercolour landscapes", list_answer="William Turner")
+
+```
+
+- With `transformers`
+```python
+from transformers import pipeline
+
+pipe = pipeline("text2text-generation", "vocabtrimmer/mt5-small-trimmed-en-5000-squad-qg")
+output = pipe("<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")
+
+```
+
+## Evaluation
+
+
+- ***Metric (Question Generation)***: [raw metric file](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-en-5000-squad-qg/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) 
+
+|            |   Score | Type    | Dataset                                                        |
+|:-----------|--------:|:--------|:---------------------------------------------------------------|
+| BERTScore  |   90.01 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_1     |   55.13 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_2     |   38.84 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_3     |   29.4  | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_4     |   22.84 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| METEOR     |   24.75 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| MoverScore |   63.43 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| ROUGE_L    |   50.34 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+
+
+
+## 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: None
+ - model: ckpts/mt5-small-trimmed-en-5000
+ - max_length: 512
+ - max_length_output: 32
+ - epoch: 15
+ - batch: 16
+ - lr: 0.001
+ - fp16: False
+ - random_seed: 1
+ - gradient_accumulation_steps: 4
+ - label_smoothing: 0.15
+
+The full configuration can be found at [fine-tuning config file](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-en-5000-squad-qg/raw/main/trainer_config.json).
+
+## Citation
+```
+@inproceedings{ushio-etal-2022-generative,
+    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
+    author = "Ushio, Asahi  and
+        Alva-Manchego, Fernando  and
+        Camacho-Collados, Jose",
+    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
+    month = dec,
+    year = "2022",
+    address = "Abu Dhabi, U.A.E.",
+    publisher = "Association for Computational Linguistics",
+}
+
+```

eval/metric.first.answer.paragraph_answer.question.lmqg_qg_squad.default.json

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+{"validation": {"Bleu_1": 0.5063801323445295, "Bleu_2": 0.3530607059413135, "Bleu_3": 0.26759200525191584, "Bleu_4": 0.20962412941736752}, "test": {"Bleu_1": 0.48018545151303244, "Bleu_2": 0.3267165556277891, "Bleu_3": 0.24295844075099318, "Bleu_4": 0.18656401938183997}}

eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json

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+{"validation": {"Bleu_1": 0.5594639883911724, "Bleu_2": 0.39991305368073865, "Bleu_3": 0.30832427560048614, "Bleu_4": 0.2447522914368893, "METEOR": 0.2587588604355952, "ROUGE_L": 0.5164769803751386, "BERTScore": 0.901992423180011, "MoverScore": 0.6462156835685916}, "test": {"Bleu_1": 0.5513062660608533, "Bleu_2": 0.3884350339847114, "Bleu_3": 0.2939935074357255, "Bleu_4": 0.22836698977059144, "METEOR": 0.2475014985993894, "ROUGE_L": 0.5034025673715345, "BERTScore": 0.9001243341797027, "MoverScore": 0.6342865188184792}}