Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`microsoft/layoutlmv3-base`](https://huggingface.co/microsoft/layoutlmv3-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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---
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license: cc-by-nc-sa-4.0
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tags:
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- generated_from_trainer
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- recall
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- f1
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- accuracy
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model-index:
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- name: layoutlmv3-finetuned-DocLayNet
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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: doc_lay_net-small
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type: doc_lay_net-small
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split: test
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args: DocLayNet_2022.08_processed_on_2023.01
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metrics:
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-
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type: precision
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value: 0.6178861788617886
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-
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-
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value: 0.7238095238095238
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-
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value: 0.6666666666666667
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value: 0.8719611021069692
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- en
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pipeline_tag: token-classification
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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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---
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language:
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- en
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license: cc-by-nc-sa-4.0
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tags:
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- generated_from_trainer
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- recall
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- f1
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- accuracy
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pipeline_tag: token-classification
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base_model: microsoft/layoutlmv3-base
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model-index:
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- name: layoutlmv3-finetuned-DocLayNet
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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: doc_lay_net-small
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type: doc_lay_net-small
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split: test
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args: DocLayNet_2022.08_processed_on_2023.01
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metrics:
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- type: precision
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value: 0.6178861788617886
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name: Precision
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- type: recall
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value: 0.7238095238095238
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name: Recall
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- type: f1
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value: 0.6666666666666667
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name: F1
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- type: accuracy
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value: 0.8719611021069692
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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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