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Librarian Bot: Add base_model information to model

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This pull request aims to enrich the metadata of your model by adding [`roberta-base`](https://huggingface.co/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!

Files changed (1) hide show
  1. README.md +25 -23
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/roberta-base-topic-single
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  results:
@@ -13,33 +31,17 @@ model-index:
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  dataset:
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  name: cardiffnlp/tweet_topic_single
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  type: cardiffnlp/tweet_topic_single
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- split: test_2021
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  metrics:
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- - name: Micro F1 (cardiffnlp/tweet_topic_single)
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- type: micro_f1_cardiffnlp/tweet_topic_single
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  value: 0.8818665091553456
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- - name: Macro F1 (cardiffnlp/tweet_topic_single)
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- type: micro_f1_cardiffnlp/tweet_topic_single
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  value: 0.7359303318518903
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- - name: Accuracy (cardiffnlp/tweet_topic_single)
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- type: accuracy_cardiffnlp/tweet_topic_single
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  value: 0.8818665091553456
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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@} 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/roberta-base-topic-single
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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: roberta-base
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  model-index:
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  - name: cardiffnlp/roberta-base-topic-single
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  results:
 
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  dataset:
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  name: cardiffnlp/tweet_topic_single
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  type: cardiffnlp/tweet_topic_single
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+ split: test_2021
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  metrics:
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+ - type: micro_f1_cardiffnlp/tweet_topic_single
 
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  value: 0.8818665091553456
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+ name: Micro F1 (cardiffnlp/tweet_topic_single)
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+ - type: micro_f1_cardiffnlp/tweet_topic_single
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  value: 0.7359303318518903
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+ name: Macro F1 (cardiffnlp/tweet_topic_single)
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+ - type: accuracy_cardiffnlp/tweet_topic_single
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  value: 0.8818665091553456
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+ name: Accuracy (cardiffnlp/tweet_topic_single)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # cardiffnlp/roberta-base-topic-single
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