Librarian Bot: Add base_model information to model
#2
by
librarian-bot
- opened
README.md
CHANGED
@@ -4,6 +4,24 @@ datasets:
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metrics:
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- f1
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- accuracy
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model-index:
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- name: cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual
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results:
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@@ -13,33 +31,17 @@ model-index:
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dataset:
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name: cardiffnlp/tweet_sentiment_multilingual
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type: all
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split: test
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metrics:
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type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
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value: 0.6169540229885058
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value: 0.6168385894019698
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value: 0.6169540229885058
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widget:
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- text: Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below {{URL}}
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example_title: "topic_classification 1"
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- text: Yes, including Medicare and social security saving👍
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example_title: "sentiment 1"
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- text: All two of them taste like ass.
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example_title: "offensive 1"
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- text: If you wanna look like a badass, have drama on social media
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example_title: "irony 1"
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- text: Whoever just unfollowed me you a bitch
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example_title: "hate 1"
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- text: I love swimming for the same reason I love meditating...the feeling of weightlessness.
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example_title: "emotion 1"
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- text: Beautiful sunset last night from the pontoon @TupperLakeNY
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example_title: "emoji 1"
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---
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# cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual
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metrics:
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- f1
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- accuracy
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pipeline_tag: text-classification
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widget:
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- text: Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@}
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via {@bluenoterecords@} link below {{URL}}
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example_title: topic_classification 1
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- text: Yes, including Medicare and social security saving👍
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example_title: sentiment 1
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- text: All two of them taste like ass.
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example_title: offensive 1
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- text: If you wanna look like a badass, have drama on social media
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example_title: irony 1
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- text: Whoever just unfollowed me you a bitch
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example_title: hate 1
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- text: I love swimming for the same reason I love meditating...the feeling of weightlessness.
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example_title: emotion 1
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- text: Beautiful sunset last night from the pontoon @TupperLakeNY
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example_title: emoji 1
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base_model: bert-base-multilingual-cased
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model-index:
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- name: cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual
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results:
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dataset:
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name: cardiffnlp/tweet_sentiment_multilingual
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type: all
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split: test
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metrics:
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- type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
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value: 0.6169540229885058
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name: Micro F1 (cardiffnlp/tweet_sentiment_multilingual/all)
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- type: micro_f1_cardiffnlp/tweet_sentiment_multilingual/all
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value: 0.6168385894019698
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name: Macro F1 (cardiffnlp/tweet_sentiment_multilingual/all)
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- type: accuracy_cardiffnlp/tweet_sentiment_multilingual/all
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value: 0.6169540229885058
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name: Accuracy (cardiffnlp/tweet_sentiment_multilingual/all)
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---
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# cardiffnlp/bert-base-multilingual-cased-sentiment-multilingual
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