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Adjust date format from Model Recycling
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README.md
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@@ -91,7 +91,7 @@ Our score (Rouge 1 score of 47.4798) puts this model's performance between fourt
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[Evaluation on 36 datasets](https://ibm.github.io/model-recycling/model_gain_chart?avg=9.04&mnli_lp=nan&20_newsgroup=3.55&ag_news=1.66&amazon_reviews_multi=0.19&anli=14.53&boolq=16.60&cb=24.91&cola=10.35&copa=25.50&dbpedia=5.73&esnli=5.31&financial_phrasebank=19.96&imdb=0.05&isear=0.59&mnli=11.74&mrpc=15.89&multirc=5.99&poem_sentiment=23.27&qnli=3.93&qqp=5.54&rotten_tomatoes=3.54&rte=23.90&sst2=-0.14&sst_5bins=5.12&stsb=20.58&trec_coarse=4.15&trec_fine=10.93&tweet_ev_emoji=12.87&tweet_ev_emotion=6.02&tweet_ev_hate=-0.04&tweet_ev_irony=7.12&tweet_ev_offensive=2.16&tweet_ev_sentiment=-0.00&wic=12.03&wnli=9.44&wsc=9.37&yahoo_answers=3.04&model_name=andreaparker%2Fflan-t5-base-samsum&base_name=google%2Ft5-v1_1-base) using andreaparker/flan-t5-base-samsum as a base model yields average score of 77.86 in comparison to 68.82 by google/t5-v1_1-base.
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The model is ranked 2nd among all tested models for the google/t5-v1_1-base architecture as of 07/
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Results:
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| 20_newsgroup | ag_news | amazon_reviews_multi | anli | boolq | cb | cola | copa | dbpedia | esnli | financial_phrasebank | imdb | isear | mnli | mrpc | multirc | poem_sentiment | qnli | qqp | rotten_tomatoes | rte | sst2 | sst_5bins | stsb | trec_coarse | trec_fine | tweet_ev_emoji | tweet_ev_emotion | tweet_ev_hate | tweet_ev_irony | tweet_ev_offensive | tweet_ev_sentiment | wic | wnli | wsc | yahoo_answers |
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[Evaluation on 36 datasets](https://ibm.github.io/model-recycling/model_gain_chart?avg=9.04&mnli_lp=nan&20_newsgroup=3.55&ag_news=1.66&amazon_reviews_multi=0.19&anli=14.53&boolq=16.60&cb=24.91&cola=10.35&copa=25.50&dbpedia=5.73&esnli=5.31&financial_phrasebank=19.96&imdb=0.05&isear=0.59&mnli=11.74&mrpc=15.89&multirc=5.99&poem_sentiment=23.27&qnli=3.93&qqp=5.54&rotten_tomatoes=3.54&rte=23.90&sst2=-0.14&sst_5bins=5.12&stsb=20.58&trec_coarse=4.15&trec_fine=10.93&tweet_ev_emoji=12.87&tweet_ev_emotion=6.02&tweet_ev_hate=-0.04&tweet_ev_irony=7.12&tweet_ev_offensive=2.16&tweet_ev_sentiment=-0.00&wic=12.03&wnli=9.44&wsc=9.37&yahoo_answers=3.04&model_name=andreaparker%2Fflan-t5-base-samsum&base_name=google%2Ft5-v1_1-base) using andreaparker/flan-t5-base-samsum as a base model yields average score of 77.86 in comparison to 68.82 by google/t5-v1_1-base.
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The model is ranked 2nd among all tested models for the google/t5-v1_1-base architecture as of 07/February/2023
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Results:
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| 20_newsgroup | ag_news | amazon_reviews_multi | anli | boolq | cb | cola | copa | dbpedia | esnli | financial_phrasebank | imdb | isear | mnli | mrpc | multirc | poem_sentiment | qnli | qqp | rotten_tomatoes | rte | sst2 | sst_5bins | stsb | trec_coarse | trec_fine | tweet_ev_emoji | tweet_ev_emotion | tweet_ev_hate | tweet_ev_irony | tweet_ev_offensive | tweet_ev_sentiment | wic | wnli | wsc | yahoo_answers |
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