Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`microsoft/deberta-v3-large`](https://huggingface.co/microsoft/deberta-v3-large) 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!
@@ -5,49 +5,49 @@ metrics:
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- f1
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- precision
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- recall
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model-index:
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- name: tner/deberta-v3-large-btc
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: tner/btc
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type: tner/btc
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args: tner/btc
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metrics:
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type: f1
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value: 0.8399238265934805
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value: 0.8237749945067018
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value: 0.8567184643510055
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value: 0.7921150390682584
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value: 0.7766126681668878
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value: 0.8103758198218992
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value: 0.9134087599417496
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value: 0.8958470665787739
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value: 0.931672760511883
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pipeline_tag: token-classification
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widget:
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- text: "Jacob Collier is a Grammy awarded artist from England."
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example_title: "NER Example 1"
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---
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# tner/deberta-v3-large-btc
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- f1
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- precision
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- recall
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pipeline_tag: token-classification
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widget:
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- text: Jacob Collier is a Grammy awarded artist from England.
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example_title: NER Example 1
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base_model: microsoft/deberta-v3-large
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model-index:
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- name: tner/deberta-v3-large-btc
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results:
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- task:
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type: token-classification
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name: Token Classification
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dataset:
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name: tner/btc
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type: tner/btc
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args: tner/btc
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metrics:
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- type: f1
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value: 0.8399238265934805
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name: F1
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- type: precision
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value: 0.8237749945067018
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name: Precision
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- type: recall
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value: 0.8567184643510055
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name: Recall
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- type: f1_macro
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value: 0.7921150390682584
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name: F1 (macro)
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- type: precision_macro
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value: 0.7766126681668878
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name: Precision (macro)
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- type: recall_macro
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value: 0.8103758198218992
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name: Recall (macro)
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- type: f1_entity_span
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value: 0.9134087599417496
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name: F1 (entity span)
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- type: precision_entity_span
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value: 0.8958470665787739
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name: Precision (entity span)
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- type: recall_entity_span
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value: 0.931672760511883
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name: Recall (entity span)
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---
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# tner/deberta-v3-large-btc
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