commit files to HF hub
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README.md
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@@ -31,33 +31,33 @@ model-index:
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metrics:
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- name: BLEU4 (Question Answering)
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type: bleu4_question_answering
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value:
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- name: ROUGE-L (Question Answering)
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type: rouge_l_question_answering
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value:
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- name: METEOR (Question Answering)
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type: meteor_question_answering
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value:
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- name: BERTScore (Question Answering)
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type: bertscore_question_answering
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value:
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- name: MoverScore (Question Answering)
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type: moverscore_question_answering
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value:
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- name: AnswerF1Score (Question Answering)
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type: answer_f1_score__question_answering
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value:
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- name: AnswerExactMatch (Question Answering)
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type: answer_exact_match_question_answering
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value:
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---
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# Model Card of `vocabtrimmer/mt5-small-trimmed-fr-90000-frquad-qa`
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This model is fine-tuned version of [
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### Overview
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- **Language model:** [
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- **Language:** fr
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- **Training data:** [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) (default)
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- **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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| | Score | Type | Dataset |
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|:-----------------|--------:|:--------|:-----------------------------------------------------------------|
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| AnswerExactMatch |
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| AnswerF1Score |
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| BERTScore |
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| Bleu_1 |
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| Bleu_2 |
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| Bleu_3 |
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| Bleu_4 |
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| METEOR |
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| MoverScore |
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| ROUGE_L |
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@@ -114,15 +114,15 @@ The following hyperparameters were used during fine-tuning:
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- input_types: ['paragraph_question']
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- output_types: ['answer']
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- prefix_types: None
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- model:
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- max_length: 512
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- max_length_output: 32
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- epoch:
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- batch: 32
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- lr: 0.
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- fp16: False
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- random_seed: 1
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- gradient_accumulation_steps:
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- label_smoothing: 0.15
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The full configuration can be found at [fine-tuning config file](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-fr-90000-frquad-qa/raw/main/trainer_config.json).
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metrics:
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- name: BLEU4 (Question Answering)
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type: bleu4_question_answering
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value: 9.96
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- name: ROUGE-L (Question Answering)
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type: rouge_l_question_answering
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value: 27.98
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- name: METEOR (Question Answering)
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type: meteor_question_answering
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value: 23.8
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- name: BERTScore (Question Answering)
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type: bertscore_question_answering
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value: 87.4
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- name: MoverScore (Question Answering)
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type: moverscore_question_answering
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value: 68.49
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- name: AnswerF1Score (Question Answering)
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type: answer_f1_score__question_answering
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value: 43.12
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- name: AnswerExactMatch (Question Answering)
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type: answer_exact_match_question_answering
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value: 24.06
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---
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# Model Card of `vocabtrimmer/mt5-small-trimmed-fr-90000-frquad-qa`
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This model is fine-tuned version of [ckpts/mt5-small-trimmed-fr-90000](https://huggingface.co/ckpts/mt5-small-trimmed-fr-90000) for question answering task on the [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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### Overview
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- **Language model:** [ckpts/mt5-small-trimmed-fr-90000](https://huggingface.co/ckpts/mt5-small-trimmed-fr-90000)
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- **Language:** fr
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- **Training data:** [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) (default)
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- **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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| | Score | Type | Dataset |
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|:-----------------|--------:|:--------|:-----------------------------------------------------------------|
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| AnswerExactMatch | 24.06 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| AnswerF1Score | 43.12 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| BERTScore | 87.4 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| Bleu_1 | 17.28 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| Bleu_2 | 14.01 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| Bleu_3 | 11.74 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| Bleu_4 | 9.96 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| METEOR | 23.8 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| MoverScore | 68.49 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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| ROUGE_L | 27.98 | default | [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad) |
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- input_types: ['paragraph_question']
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- output_types: ['answer']
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- prefix_types: None
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- model: ckpts/mt5-small-trimmed-fr-90000
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- max_length: 512
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- max_length_output: 32
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- epoch: 13
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- batch: 32
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- lr: 0.001
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- fp16: False
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- random_seed: 1
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- gradient_accumulation_steps: 2
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- label_smoothing: 0.15
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The full configuration can be found at [fine-tuning config file](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-fr-90000-frquad-qa/raw/main/trainer_config.json).
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eval/metric.first.answer.paragraph_question.answer.lmqg_qg_frquad.default.json
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{"validation": {"Bleu_1":
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{"validation": {"Bleu_1": 0.1932725401837919, "Bleu_2": 0.16007914602896, "Bleu_3": 0.13578319438973033, "Bleu_4": 0.116296643168242, "METEOR": 0.2336239495477666, "ROUGE_L": 0.2869036816616231, "BERTScore": 0.8729169056511284, "MoverScore": 0.6741014345784797, "AnswerF1Score": 42.11315829622192, "AnswerExactMatch": 19.69887076537014}, "test": {"Bleu_1": 0.17281853864733646, "Bleu_2": 0.14009403051623157, "Bleu_3": 0.11740903841504663, "Bleu_4": 0.09957940417233394, "METEOR": 0.23798691012437684, "ROUGE_L": 0.27980331642769446, "BERTScore": 0.8740178610442424, "MoverScore": 0.6849181722997052, "AnswerF1Score": 43.11839268944033, "AnswerExactMatch": 24.058971141781683}}
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eval/samples.test.hyp.paragraph_question.answer.lmqg_qg_frquad.default.txt
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eval/samples.validation.hyp.paragraph_question.answer.lmqg_qg_frquad.default.txt
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