Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`Wav2Vec2-XLS-R-300M`](https://huggingface.co/Wav2Vec2-XLS-R-300M) 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)!
@@ -8,48 +8,49 @@ tags:
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- robust-speech-event
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datasets:
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- kresnik/zeroth_korean
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model-index:
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- name: Wav2Vec2 XLS-R 300M Korean
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Zeroth Korean
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type: kresnik/zeroth_korean
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args: clean
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metrics:
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-
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type: wer
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value: 29.54
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value: 9.53
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Robust Speech Event - Dev Data
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type: speech-recognition-community-v2/dev_data
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args: ko
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metrics:
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-
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type: wer
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value: 76.26
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-
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value: 38.67
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Robust Speech Event - Test Data
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type: speech-recognition-community-v2/eval_data
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args: ko
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metrics:
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-
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type: wer
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value: 73.18
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---
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# Wav2Vec2 XLS-R 300M Korean
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- robust-speech-event
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datasets:
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- kresnik/zeroth_korean
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+
base_model: Wav2Vec2-XLS-R-300M
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model-index:
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- name: Wav2Vec2 XLS-R 300M Korean
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results:
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- task:
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type: automatic-speech-recognition
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+
name: Automatic Speech Recognition
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dataset:
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name: Zeroth Korean
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type: kresnik/zeroth_korean
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args: clean
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metrics:
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+
- type: wer
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value: 29.54
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+
name: Test WER
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+
- type: cer
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value: 9.53
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+
name: Test CER
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- task:
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type: automatic-speech-recognition
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+
name: Automatic Speech Recognition
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dataset:
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name: Robust Speech Event - Dev Data
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type: speech-recognition-community-v2/dev_data
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args: ko
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metrics:
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+
- type: wer
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value: 76.26
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+
name: Test WER
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+
- type: cer
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value: 38.67
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+
name: Test CER
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- task:
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type: automatic-speech-recognition
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+
name: Automatic Speech Recognition
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dataset:
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name: Robust Speech Event - Test Data
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type: speech-recognition-community-v2/eval_data
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args: ko
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metrics:
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+
- type: wer
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value: 73.18
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+
name: Test WER
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---
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# Wav2Vec2 XLS-R 300M Korean
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