Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`cardiffnlp/twitter-xlm-roberta-base`](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.
How did we find this information? We performed a regular expression match on your `README.md` file to determine the connection.
**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.
For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).
This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien). Your input is invaluable to us!
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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/twitter-xlm-roberta-base-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: 0.6931034482758621
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value: 0.692628774202147
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value: 0.6931034482758621
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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/twitter-xlm-roberta-base-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: cardiffnlp/twitter-xlm-roberta-base
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model-index:
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- name: cardiffnlp/twitter-xlm-roberta-base-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: 0.6931034482758621
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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: 0.692628774202147
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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: 0.6931034482758621
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name: Accuracy (cardiffnlp/tweet_sentiment_multilingual/all)
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---
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# cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual
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