Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`bert-base-uncased`](https://huggingface.co/bert-base-uncased) 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: apache-2.0
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language: en
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-
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- Jzuluaga/uwb_atcc
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tags:
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- text
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- token-classification
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- generated_from_trainer
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- bert
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- bertraffic
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metrics:
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- Precision
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- Recall
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- F1
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- Jaccard Error Rate
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widget:
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- text:
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- text:
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model-index:
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- name: bert-base-token-classification-for-atc-en-uwb-atcc
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results:
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- task:
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dataset:
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metrics:
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- type: F1
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value: 0.87
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name: TEST F1 (macro)
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verified:
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- type: Accuracy
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value: 0.91
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name: TEST Accuracy
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verified:
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- type: Precision
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value: 0.86
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name: TEST Precision (macro)
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verified:
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- type: Recall
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value: 0.88
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name: TEST Recall (macro)
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verified:
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- type: Jaccard Error Rate
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value: 0.169
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name: TEST Jaccard Error Rate
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verified:
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---
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# bert-base-token-classification-for-atc-en-uwb-atcc
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---
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language: en
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+
license: apache-2.0
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tags:
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- text
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- token-classification
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- generated_from_trainer
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- bert
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- bertraffic
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datasets:
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- Jzuluaga/uwb_atcc
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metrics:
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- Precision
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- Recall
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- F1
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- Jaccard Error Rate
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widget:
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- text: lining up runway three one csa five bravo easy five three kilo romeo contact
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ruzyne ground one two one decimal nine good bye
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- text: csa seven three two zero so change of taxi quality eight nine sierra we need
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to full length britair five nine zero bravo contact ruzyne ground one two one
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decimal nine good bye
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- text: swiss four six one foxtrot line up runway three one and wait one two one nine
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csa four yankee alfa
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- text: tower klm five five tango ils three one wizz air four papa uniform tower roger
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base_model: bert-base-uncased
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model-index:
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- name: bert-base-token-classification-for-atc-en-uwb-atcc
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results:
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- task:
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type: token-classification
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name: chunking
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dataset:
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name: UWB-ATCC corpus (Air Traffic Control Communications)
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type: Jzuluaga/uwb_atcc
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config: test
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split: test
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metrics:
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- type: F1
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value: 0.87
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name: TEST F1 (macro)
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verified: false
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- type: Accuracy
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value: 0.91
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name: TEST Accuracy
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verified: false
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- type: Precision
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value: 0.86
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name: TEST Precision (macro)
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verified: false
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- type: Recall
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value: 0.88
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name: TEST Recall (macro)
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verified: false
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- type: Jaccard Error Rate
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value: 0.169
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name: TEST Jaccard Error Rate
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verified: false
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---
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# bert-base-token-classification-for-atc-en-uwb-atcc
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