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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_zhquad
+pipeline_tag: text2text-generation
+tags:
+- answer extraction
+widget:
+- text: "<hl> Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress."
+  example_title: "Answering Extraction Example 1" 
+- text: "Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress. <hl>"
+  example_title: "Answering Extraction Example 2" 
+model-index:
+- name: lmqg/mt5-small-zhquad-ae
+  results:
+  - task:
+      name: Text2text Generation
+      type: text2text-generation
+    dataset:
+      name: lmqg/qg_zhquad
+      type: default
+      args: default
+    metrics:
+    - name: BLEU4 (Answer Extraction)
+      type: bleu4_answer_extraction
+      value: 82.12
+    - name: ROUGE-L (Answer Extraction)
+      type: rouge_l_answer_extraction
+      value: 95.7
+    - name: METEOR (Answer Extraction)
+      type: meteor_answer_extraction
+      value: 70.98
+    - name: BERTScore (Answer Extraction)
+      type: bertscore_answer_extraction
+      value: 99.78
+    - name: MoverScore (Answer Extraction)
+      type: moverscore_answer_extraction
+      value: 98.8
+    - name: AnswerF1Score (Answer Extraction)
+      type: answer_f1_score__answer_extraction
+      value: 95.17
+    - name: AnswerExactMatch (Answer Extraction)
+      type: answer_exact_match_answer_extraction
+      value: 95.08
+---
+
+# Model Card of `lmqg/mt5-small-zhquad-ae`
+This model is fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) for answer extraction on the [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
+
+
+### Overview
+- **Language model:** [google/mt5-small](https://huggingface.co/google/mt5-small)   
+- **Language:** en  
+- **Training data:** [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) (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="lmqg/mt5-small-zhquad-ae")
+
+# model prediction
+answers = model.generate_a("William Turner was an English painter who specialised in watercolour landscapes")
+
+```
+
+- With `transformers`
+```python
+from transformers import pipeline
+
+pipe = pipeline("text2text-generation", "lmqg/mt5-small-zhquad-ae")
+output = pipe("<hl> Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress.")
+
+```
+
+## Evaluation
+
+
+- ***Metric (Answer Extraction)***: [raw metric file](https://huggingface.co/lmqg/mt5-small-zhquad-ae/raw/main/eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_zhquad.default.json) 
+
+|                  |   Score | Type    | Dataset                                                          |
+|:-----------------|--------:|:--------|:-----------------------------------------------------------------|
+| AnswerExactMatch |   95.08 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| AnswerF1Score    |   95.17 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| BERTScore        |   99.78 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| Bleu_1           |   92.07 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| Bleu_2           |   88.98 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| Bleu_3           |   85.68 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| Bleu_4           |   82.12 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| METEOR           |   70.98 | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| MoverScore       |   98.8  | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+| ROUGE_L          |   95.7  | default | [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) |
+
+
+
+## Training hyperparameters
+
+The following hyperparameters were used during fine-tuning:
+ - dataset_path: lmqg/qg_zhquad
+ - dataset_name: default
+ - input_types: ['paragraph_sentence']
+ - output_types: ['answer']
+ - prefix_types: None
+ - model: google/mt5-small
+ - max_length: 512
+ - max_length_output: 32
+ - epoch: 4
+ - batch: 16
+ - lr: 0.0005
+ - 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/lmqg/mt5-small-zhquad-ae/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_sentence.answer.lmqg_qg_zhquad.default.json

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+{"validation": {"Bleu_1": 0.912896580140053, "Bleu_2": 0.8804701193017836, "Bleu_3": 0.8467998054794517, "Bleu_4": 0.8113598119994743, "METEOR": 0.7055339995152433, "ROUGE_L": 0.950296585648165, "BERTScore": 0.9965133804569203, "MoverScore": 0.9843137525598916, "AnswerF1Score": 94.37559263627745, "AnswerExactMatch": 94.22049538610976}, "test": {"Bleu_1": 0.9206505036707819, "Bleu_2": 0.889804563393523, "Bleu_3": 0.85680409086929, "Bleu_4": 0.8212311960361648, "METEOR": 0.7097847456378461, "ROUGE_L": 0.9569663634480098, "BERTScore": 0.9977623556187397, "MoverScore": 0.9879534864147735, "AnswerF1Score": 95.17148870232893, "AnswerExactMatch": 95.082564351627}}