model update

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:
+- 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/flan-t5-base-squad-ae
+  results:
+  - task:
+      name: Text2text Generation
+      type: text2text-generation
+    dataset:
+      name: lmqg/qg_squad
+      type: default
+      args: default
+    metrics:
+    - name: BLEU4 (Answer Extraction)
+      type: bleu4_answer_extraction
+      value: 44.15
+    - name: ROUGE-L (Answer Extraction)
+      type: rouge_l_answer_extraction
+      value: 68.88
+    - name: METEOR (Answer Extraction)
+      type: meteor_answer_extraction
+      value: 43.3
+    - name: BERTScore (Answer Extraction)
+      type: bertscore_answer_extraction
+      value: 91.56
+    - name: MoverScore (Answer Extraction)
+      type: moverscore_answer_extraction
+      value: 81.79
+    - name: AnswerF1Score (Answer Extraction)
+      type: answer_f1_score__answer_extraction
+      value: 69.41
+    - name: AnswerExactMatch (Answer Extraction)
+      type: answer_exact_match_answer_extraction
+      value: 58.16
+---
+
+# Model Card of `lmqg/flan-t5-base-squad-ae`
+This model is fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) 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:** [google/flan-t5-base](https://huggingface.co/google/flan-t5-base)   
+- **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/flan-t5-base-squad-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/flan-t5-base-squad-ae")
+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/flan-t5-base-squad-ae/raw/main/eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_squad.default.json) 
+
+|                  |   Score | Type    | Dataset                                                        |
+|:-----------------|--------:|:--------|:---------------------------------------------------------------|
+| AnswerExactMatch |   58.16 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| AnswerF1Score    |   69.41 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| BERTScore        |   91.56 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_1           |   56.8  | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_2           |   52.39 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_3           |   48.02 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| Bleu_4           |   44.15 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| METEOR           |   43.3  | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| MoverScore       |   81.79 | default | [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) |
+| ROUGE_L          |   68.88 | 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: google/flan-t5-base
+ - max_length: 512
+ - max_length_output: 32
+ - epoch: 8
+ - batch: 16
+ - lr: 0.0001
+ - 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/flan-t5-base-squad-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",
+}
+
+```

added_tokens.json

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+{
+  "<hl>": 32100
+}

config.json

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+{
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+  "add_prefix": true,
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
+    "summarization": {
+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4,
+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.21.2",
+  "use_cache": true,
+  "vocab_size": 32101
+}

eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_squad.default.json

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+{"validation": {"Bleu_1": 0.5107362944324688, "Bleu_2": 0.46847351711115787, "Bleu_3": 0.4267252954524731, "Bleu_4": 0.3895523369404056, "METEOR": 0.40637457015242434, "ROUGE_L": 0.645770150227703, "BERTScore": 0.9119154193374269, "MoverScore": 0.7860523724146663, "AnswerF1Score": 65.20614496583396, "AnswerExactMatch": 51.19205298013245}, "test": {"Bleu_1": 0.5679610571472901, "Bleu_2": 0.5239227721702817, "Bleu_3": 0.48018117612667777, "Bleu_4": 0.4415458717756335, "METEOR": 0.432999656475851, "ROUGE_L": 0.6887907527195755, "BERTScore": 0.9156043644534364, "MoverScore": 0.8178721482165371, "AnswerF1Score": 69.41163918158276, "AnswerExactMatch": 58.16283573292919}}

pytorch_model.bin

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special_tokens_map.json

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spiece.model

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tokenizer_config.json

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trainer_config.json

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+{"dataset_path": "lmqg/qg_squad", "dataset_name": "default", "input_types": ["paragraph_sentence"], "output_types": ["answer"], "prefix_types": ["ae"], "model": "google/flan-t5-base", "max_length": 512, "max_length_output": 32, "epoch": 8, "batch": 16, "lr": 0.0001, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 4, "label_smoothing": 0.15}