model update

README.md

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+
+---
+license: cc-by-4.0
+metrics:
+- bleu4
+- meteor
+- rouge-l
+- bertscore
+- moverscore
+language: it
+datasets:
+- lmqg/qg_itquad
+pipeline_tag: text2text-generation
+tags:
+- answer extraction
+widget:
+- text: "<hl> Il 6 ottobre 1973 , la Siria e l' Egitto, con il sostegno di altre nazioni arabe, lanciarono un attacco a sorpresa su Israele, su Yom Kippur. <hl> Questo rinnovo delle ostilità nel conflitto arabo-israeliano ha liberato la pressione economica sottostante sui prezzi del petrolio. All' epoca, l' Iran era il secondo esportatore mondiale di petrolio e un vicino alleato degli Stati Uniti. Settimane più tardi, lo scià d' Iran ha detto in un' intervista: Naturalmente[il prezzo del petrolio] sta andando a salire Certamente! E come! Avete[Paesi occidentali] aumentato il prezzo del grano che ci vendete del 300 per cento, e lo stesso per zucchero e cemento."
+  example_title: "Answering Extraction Example 1" 
+- text: "<hl> Furono introdotti autocarri compatti, come la Toyota Hilux e il Datsun Truck, seguiti dal camion Mazda (venduto come il Ford Courier), e l' Isuzu costruito Chevrolet LUV. <hl> Mitsubishi rebranded il suo Forte come Dodge D-50 pochi anni dopo la crisi petrolifera. Mazda, Mitsubishi e Isuzu avevano partnership congiunte rispettivamente con Ford, Chrysler e GM. In seguito i produttori americani introdussero le loro sostituzioni nazionali (Ford Ranger, Dodge Dakota e la Chevrolet S10/GMC S-15), ponendo fine alla loro politica di importazione vincolata."
+  example_title: "Answering Extraction Example 2" 
+model-index:
+- name: lmqg/mt5-base-itquad-ae
+  results:
+  - task:
+      name: Text2text Generation
+      type: text2text-generation
+    dataset:
+      name: lmqg/qg_itquad
+      type: default
+      args: default
+    metrics:
+    - name: BLEU4 (Answer Extraction)
+      type: bleu4_answer_extraction
+      value: 22.67
+    - name: ROUGE-L (Answer Extraction)
+      type: rouge_l_answer_extraction
+      value: 42.58
+    - name: METEOR (Answer Extraction)
+      type: meteor_answer_extraction
+      value: 37.72
+    - name: BERTScore (Answer Extraction)
+      type: bertscore_answer_extraction
+      value: 89.26
+    - name: MoverScore (Answer Extraction)
+      type: moverscore_answer_extraction
+      value: 78.79
+    - name: AnswerF1Score (Answer Extraction)
+      type: answer_f1_score__answer_extraction
+      value: 68.09
+    - name: AnswerExactMatch (Answer Extraction)
+      type: answer_exact_match_answer_extraction
+      value: 52.15
+---
+
+# Model Card of `lmqg/mt5-base-itquad-ae`
+This model is fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) for answer extraction on the [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
+
+
+### Overview
+- **Language model:** [google/mt5-base](https://huggingface.co/google/mt5-base)   
+- **Language:** it  
+- **Training data:** [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (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="it", model="lmqg/mt5-base-itquad-ae")
+
+# model prediction
+answers = model.generate_a("Dopo il 1971 , l' OPEC ha tardato ad adeguare i prezzi per riflettere tale deprezzamento.")
+
+```
+
+- With `transformers`
+```python
+from transformers import pipeline
+
+pipe = pipeline("text2text-generation", "lmqg/mt5-base-itquad-ae")
+output = pipe("<hl> Il 6 ottobre 1973 , la Siria e l' Egitto, con il sostegno di altre nazioni arabe, lanciarono un attacco a sorpresa su Israele, su Yom Kippur. <hl> Questo rinnovo delle ostilità nel conflitto arabo-israeliano ha liberato la pressione economica sottostante sui prezzi del petrolio. All' epoca, l' Iran era il secondo esportatore mondiale di petrolio e un vicino alleato degli Stati Uniti. Settimane più tardi, lo scià d' Iran ha detto in un' intervista: Naturalmente[il prezzo del petrolio] sta andando a salire Certamente! E come! Avete[Paesi occidentali] aumentato il prezzo del grano che ci vendete del 300 per cento, e lo stesso per zucchero e cemento.")
+
+```
+
+## Evaluation
+
+
+- ***Metric (Answer Extraction)***: [raw metric file](https://huggingface.co/lmqg/mt5-base-itquad-ae/raw/main/eval/metric.first.answer.paragraph_sentence.answer.lmqg_qg_itquad.default.json) 
+
+|                  |   Score | Type    | Dataset                                                          |
+|:-----------------|--------:|:--------|:-----------------------------------------------------------------|
+| AnswerExactMatch |   52.15 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| AnswerF1Score    |   68.09 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| BERTScore        |   89.26 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_1           |   36.69 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_2           |   30.79 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_3           |   26.51 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_4           |   22.67 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| METEOR           |   37.72 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| MoverScore       |   78.79 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| ROUGE_L          |   42.58 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+
+
+
+## Training hyperparameters
+
+The following hyperparameters were used during fine-tuning:
+ - dataset_path: lmqg/qg_itquad
+ - dataset_name: default
+ - input_types: ['paragraph_sentence']
+ - output_types: ['answer']
+ - prefix_types: None
+ - model: google/mt5-base
+ - max_length: 512
+ - max_length_output: 32
+ - epoch: 16
+ - batch: 8
+ - lr: 0.001
+ - fp16: False
+ - random_seed: 1
+ - gradient_accumulation_steps: 8
+ - label_smoothing: 0.15
+
+The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/mt5-base-itquad-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",
+}
+
+```

config.json

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 {
-  "_name_or_path": "lmqg_output/mt5-base-itquad-ae/best_model",
+  "_name_or_path": "lmqg_output/mt5-base-itquad-ae/model_ijgkkr/epoch_15",
   "add_prefix": false,
   "architectures": [
     "MT5ForConditionalGeneration"

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

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+{"validation": {"Bleu_1": 0.3613615374466616, "Bleu_2": 0.29979101174184014, "Bleu_3": 0.2572079920111839, "Bleu_4": 0.2188756857549235, "METEOR": 0.40334586128894945, "ROUGE_L": 0.42268562907901547, "BERTScore": 0.9108938501626626, "MoverScore": 0.8239377626899412, "AnswerF1Score": 73.43484666575796, "AnswerExactMatch": 60.38901301090814}, "test": {"Bleu_1": 0.36694598112592064, "Bleu_2": 0.3079147476086298, "Bleu_3": 0.26509275277318584, "Bleu_4": 0.22667978095566216, "METEOR": 0.3771853045500855, "ROUGE_L": 0.4258455498245661, "BERTScore": 0.8926223951298486, "MoverScore": 0.7878688802080305, "AnswerF1Score": 68.09132800296655, "AnswerExactMatch": 52.14877119200946}}

pytorch_model.bin

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+size 2329634869

tokenizer_config.json

@@ -2,7 +2,7 @@
   "additional_special_tokens": null,
   "eos_token": "</s>",
   "extra_ids": 0,
-  "name_or_path": "lmqg_output/mt5-base-itquad-ae/best_model",
+  "name_or_path": "lmqg_output/mt5-base-itquad-ae/model_ijgkkr/epoch_15",
   "pad_token": "<pad>",
   "sp_model_kwargs": {},
   "special_tokens_map_file": "/home/patrick/.cache/torch/transformers/685ac0ca8568ec593a48b61b0a3c272beee9bc194a3c7241d15dcadb5f875e53.f76030f3ec1b96a8199b2593390c610e76ca8028ef3d24680000619ffb646276",

trainer_config.json

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+{"dataset_path": "lmqg/qg_itquad", "dataset_name": "default", "input_types": ["paragraph_sentence"], "output_types": ["answer"], "prefix_types": null, "model": "google/mt5-base", "max_length": 512, "max_length_output": 32, "epoch": 16, "batch": 8, "lr": 0.001, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 8, "label_smoothing": 0.15}