commit files to HF hub
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README.md
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@@ -31,25 +31,25 @@ 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-ko-30000-koquad-qa`
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@@ -93,16 +93,16 @@ output = pipe("question: 매드 클라운이 참가해 큰 화제를 모았던
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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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@@ -118,11 +118,11 @@ The following hyperparameters were used during fine-tuning:
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- max_length: 512
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- max_length_output: 32
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- epoch: 5
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- batch:
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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:
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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-ko-30000-koquad-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: 31.34
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- name: ROUGE-L (Question Answering)
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type: rouge_l_question_answering
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value: 70.66
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- name: METEOR (Question Answering)
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type: meteor_question_answering
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value: 50.53
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- name: BERTScore (Question Answering)
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type: bertscore_question_answering
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value: 96.27
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- name: MoverScore (Question Answering)
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type: moverscore_question_answering
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value: 90.04
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- name: AnswerF1Score (Question Answering)
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type: answer_f1_score__question_answering
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value: 74.71
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- name: AnswerExactMatch (Question Answering)
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type: answer_exact_match_question_answering
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value: 68.16
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---
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# Model Card of `vocabtrimmer/mt5-small-trimmed-ko-30000-koquad-qa`
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| | Score | Type | Dataset |
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|:-----------------|--------:|:--------|:-----------------------------------------------------------------|
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| AnswerExactMatch | 68.16 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| AnswerF1Score | 74.71 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| BERTScore | 96.27 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| Bleu_1 | 64.73 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| Bleu_2 | 56.16 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| Bleu_3 | 45.24 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| Bleu_4 | 31.34 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| METEOR | 50.53 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| MoverScore | 90.04 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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| ROUGE_L | 70.66 | default | [lmqg/qg_koquad](https://huggingface.co/datasets/lmqg/qg_koquad) |
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- max_length: 512
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- max_length_output: 32
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- epoch: 5
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- batch: 64
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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: 1
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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-ko-30000-koquad-qa/raw/main/trainer_config.json).
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eval/metric.first.answer.paragraph_question.answer.lmqg_qg_koquad.default.json
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{"validation": {"Bleu_1": 0.
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{"validation": {"Bleu_1": 0.6537011097941328, "Bleu_2": 0.5735758572983447, "Bleu_3": 0.4767258223922961, "Bleu_4": 0.3453850019905082, "METEOR": 0.5026406437140047, "ROUGE_L": 0.6970146393881299, "BERTScore": 0.9623686538113102, "MoverScore": 0.8978806396080128, "AnswerF1Score": 73.82546289414114, "AnswerExactMatch": 66.89212625737079}, "test": {"Bleu_1": 0.6472518457751592, "Bleu_2": 0.5615554084794614, "Bleu_3": 0.4523617968173102, "Bleu_4": 0.31339085747018447, "METEOR": 0.5052834772276389, "ROUGE_L": 0.7066270889175926, "BERTScore": 0.9626775134407808, "MoverScore": 0.9004137617009108, "AnswerF1Score": 74.70867716705372, "AnswerExactMatch": 68.15816857440167}}
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eval/samples.test.hyp.paragraph_question.answer.lmqg_qg_koquad.default.txt
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eval/samples.validation.hyp.paragraph_question.answer.lmqg_qg_koquad.default.txt
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