Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`vesteinn/IceBERT`](https://huggingface.co/vesteinn/IceBERT) 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).
If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!
@@ -11,29 +11,30 @@ metrics:
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- accuracy
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widget:
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- text: Bob Dillan beit Maríu Markan á barkann.
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model-index:
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- name: IceBERT-finetuned-ner
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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: mim_gold_ner
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type: mim_gold_ner
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args: mim-gold-ner
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metrics:
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type: precision
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value: 0.8873049035270985
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value: 0.8627076114231091
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value: 0.8748333939173634
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value: 0.9848076353832492
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- accuracy
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widget:
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- text: Bob Dillan beit Maríu Markan á barkann.
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base_model: vesteinn/IceBERT
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model-index:
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- name: IceBERT-finetuned-ner
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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: mim_gold_ner
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type: mim_gold_ner
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args: mim-gold-ner
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metrics:
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- type: precision
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value: 0.8873049035270985
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name: Precision
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- type: recall
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value: 0.8627076114231091
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name: Recall
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- type: f1
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value: 0.8748333939173634
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name: F1
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- type: accuracy
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value: 0.9848076353832492
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name: Accuracy
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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