model update

README.md

@@ -0,0 +1,144 @@
+
+---
+license: cc-by-4.0
+metrics:
+- bleu4
+- meteor
+- rouge-l
+- bertscore
+- moverscore
+language: en
+datasets:
+- lmqg/qg_squad
+pipeline_tag: text2text-generation
+tags:
+- answer extraction
+widget:
+- text: "extract answers: <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: "extract answers: 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/t5-small-squad-answer-extraction
+  results:
+  - task:
+      name: Text2text Generation
+      type: text2text-generation
+    dataset:
+      name: lmqg/qg_squad
+      type: default
+      args: default
+    metrics:
+    - name: BLEU4
+      type: bleu4
+      value: 39.23
+    - name: ROUGE-L
+      type: rouge-l
+      value: 67.58
+    - name: METEOR
+      type: meteor
+      value: 42.5
+    - name: BERTScore
+      type: bertscore
+      value: 91.2
+    - name: MoverScore
+      type: moverscore
+      value: 80.92
+    - name: AnswerF1Score (Answer Extraction)
+      type: answer_f1_score_answer_extraction
+      value: 68.06
+    - name: AnswerExactMatch (Answer Extraction)
+      type: answer_exact_match_answer_extraction
+      value: 56.15
+---
+
+# Model Card of `lmqg/t5-small-squad-answer-extraction`
+This model is fine-tuned version of [t5-small](https://huggingface.co/t5-small) for answer extraction 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:** [t5-small](https://huggingface.co/t5-small)   
+- **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="lmqg/t5-small-squad-answer-extraction")
+
+# 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/t5-small-squad-answer-extraction")
+output = pipe("extract answers: <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/t5-small-squad-answer-extraction/raw/main/eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_squad.default.json) 
+
+|                  |   Score | Type    | Dataset                                                        |
+|:-----------------|--------:|:--------|:---------------------------------------------------------------|
+| AnswerExactMatch |   56.15 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| AnswerF1Score    |   68.06 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| BERTScore        |   91.2  | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_1           |   52.42 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_2           |   47.81 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_3           |   43.22 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_4           |   39.23 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| METEOR           |   42.5  | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| MoverScore       |   80.92 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| ROUGE_L          |   67.58 | 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_sentence']
+ - output_types: ['answer']
+ - prefix_types: ['ae']
+ - model: t5-small
+ - max_length: 512
+ - max_length_output: 32
+ - epoch: 7
+ - batch: 64
+ - lr: 0.0001
+ - fp16: False
+ - random_seed: 1
+ - gradient_accumulation_steps: 1
+ - label_smoothing: 0.15
+
+The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/t5-small-squad-answer-extraction/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",
+}
+
+```

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "lmqg_output/t5-small-squad-answer-extraction/best_model",
+  "_name_or_path": "lmqg_output/t5-small-squad-answer-extraction/model_eszyci/epoch_2",
   "add_prefix": true,
   "architectures": [
     "T5ForConditionalGeneration"

pytorch_model.bin

@@ -1,3 +1,3 @@
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+size 242016345

tokenizer_config.json

@@ -104,7 +104,7 @@
   "eos_token": "</s>",
   "extra_ids": 100,
   "model_max_length": 512,
-  "name_or_path": "lmqg_output/t5-small-squad-answer-extraction/best_model",
+  "name_or_path": "lmqg_output/t5-small-squad-answer-extraction/model_eszyci/epoch_2",
   "pad_token": "<pad>",
   "special_tokens_map_file": null,
   "tokenizer_class": "T5Tokenizer",