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Librarian Bot: Add base_model information to model

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This pull request aims to enrich the metadata of your model by adding [`facebook/wav2vec2-xls-r-300m`](https://huggingface.co/facebook/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)!

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  1. README.md +13 -12
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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- license: apache-2.0
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  language:
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  - es
 
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  tags:
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  - es
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  - generated_from_trainer
@@ -9,45 +9,46 @@ tags:
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  - robust-speech-event
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  datasets:
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  - common_voice
 
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  model-index:
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  - name: wav2vec2-xls-r-300m-36-tokens-with-lm-es
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  results:
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  - task:
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- name: Speech Recognition
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  type: automatic-speech-recognition
 
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  dataset:
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  name: common_voice es
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  type: common_voice
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  args: es
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  metrics:
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- - name: Test WER
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- type: wer
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  value: 0.08677014042867702
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- - name: Test CER
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- type: cer
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  value: 0.02810974186831335
 
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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: es
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  metrics:
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- - name: Test WER
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- type: wer
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  value: 31.68
 
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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: es
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  metrics:
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- - name: Test WER
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- type: wer
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  value: 34.45
 
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  ---
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  # Wav2Vec2-xls-r-300m-36-tokens-with-lm-es
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  ---
 
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  language:
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  - es
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+ license: apache-2.0
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  tags:
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  - es
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  - generated_from_trainer
 
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  - robust-speech-event
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  datasets:
11
  - common_voice
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+ base_model: facebook/wav2vec2-xls-r-300m
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  model-index:
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  - name: wav2vec2-xls-r-300m-36-tokens-with-lm-es
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  results:
16
  - task:
 
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  type: automatic-speech-recognition
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+ name: Speech Recognition
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  dataset:
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  name: common_voice es
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  type: common_voice
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  args: es
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  metrics:
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+ - type: wer
 
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  value: 0.08677014042867702
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+ name: Test WER
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+ - type: cer
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  value: 0.02810974186831335
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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: es
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  metrics:
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+ - type: wer
 
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  value: 31.68
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+ name: Test WER
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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: es
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  metrics:
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+ - type: wer
 
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  value: 34.45
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+ name: Test WER
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  ---
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  # Wav2Vec2-xls-r-300m-36-tokens-with-lm-es
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