model update

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "lmqg_output/mt5_small_esquad_answer/best_model",
+  "_name_or_path": "google/mt5-small",
   "add_prefix": true,
   "architectures": [
     "MT5ForConditionalGeneration"

eval/metric.first.answer.paragraph_answer.question.asahi417_qg_esquad.default.json

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eval/metric.first.answer.paragraph_sentence.question.asahi417_qg_esquad.default.json

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eval/metric.first.answer.sentence_answer.question.asahi417_qg_esquad.default.json

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+{"validation": {"Bleu_1": 0.2090463715850695, "Bleu_2": 0.13238713926513807, "Bleu_3": 0.09255897673564045, "Bleu_4": 0.067829296348406, "METEOR": 0.17905581184999808, "ROUGE_L": 0.18948777577559947, "BERTScore": 0.8125919099731499}, "test": {"Bleu_1": 0.20503846420403177, "Bleu_2": 0.12915421162526503, "Bleu_3": 0.08954756545536438, "Bleu_4": 0.06499777030248055, "METEOR": 0.17791216425018017, "ROUGE_L": 0.1875037092678093, "BERTScore": 0.8123209236247876}}

eval/metric.first.sentence.paragraph_answer.question.asahi417_qg_esquad.default.json

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+{"validation": {"Bleu_1": 0.25619431442357854, "Bleu_2": 0.17339284743221706, "Bleu_3": 0.1255028310679963, "Bleu_4": 0.09357581348401116, "METEOR": 0.2187418127136501, "ROUGE_L": 0.23824144741790626, "BERTScore": 0.8321882487838327}, "test": {"Bleu_1": 0.2450452582381805, "Bleu_2": 0.16478025971436297, "Bleu_3": 0.11834457863127808, "Bleu_4": 0.08785998455701795, "METEOR": 0.21658762330370077, "ROUGE_L": 0.231305383218115, "BERTScore": 0.8339217841152116}}

eval/metric.first.sentence.paragraph_sentence.question.asahi417_qg_esquad.default.json

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eval/metric.first.sentence.sentence_answer.question.asahi417_qg_esquad.default.json

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eval/metric.last.sentence.paragraph_answer.question.asahi417_qg_esquad.default.json

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eval/metric.last.sentence.paragraph_sentence.question.asahi417_qg_esquad.default.json

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eval/metric.last.sentence.sentence_answer.question.asahi417_qg_esquad.default.json

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eval/metric.long.sentence.paragraph_answer.question.asahi417_qg_esquad.default.json

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eval/metric.long.sentence.paragraph_sentence.question.asahi417_qg_esquad.default.json

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eval/metric.long.sentence.sentence_answer.question.asahi417_qg_esquad.default.json

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eval/metric.middle.sentence.paragraph_answer.question.asahi417_qg_esquad.default.json

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eval/metric.middle.sentence.paragraph_sentence.question.asahi417_qg_esquad.default.json

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eval/metric.middle.sentence.sentence_answer.question.asahi417_qg_esquad.default.json

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eval/metric.short.sentence.paragraph_answer.question.asahi417_qg_esquad.default.json

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eval/metric.short.sentence.paragraph_sentence.question.asahi417_qg_esquad.default.json

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eval/metric.short.sentence.sentence_answer.question.asahi417_qg_esquad.default.json

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pytorch_model.bin

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tokenizer.json

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tokenizer_config.json

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trainer_config.json

@@ -0,0 +1 @@
+{"dataset_path": "asahi417/qg_esquad", "dataset_name": "default", "input_types": ["paragraph_answer", "paragraph_sentence"], "output_types": ["question", "answer"], "prefix_types": ["qg", "ae"], "model": "google/mt5-small", "max_length": 512, "max_length_output": 32, "epoch": 5, "batch": 16, "lr": 0.001, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 4, "label_smoothing": 0.15}