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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 [`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)!

Files changed (1) hide show
  1. README.md +14 -13
README.md CHANGED
@@ -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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- - name: Test WER
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- type: wer
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  value: 29.54
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- - name: Test CER
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- type: cer
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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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- - name: Test WER
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- type: wer
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  value: 76.26
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- - name: Test CER
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- type: cer
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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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- - name: Test WER
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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
9
  datasets:
10
  - kresnik/zeroth_korean
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+ base_model: Wav2Vec2-XLS-R-300M
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  model-index:
13
  - name: Wav2Vec2 XLS-R 300M Korean
14
  results:
15
  - task:
 
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  type: automatic-speech-recognition
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+ name: Automatic Speech Recognition
18
  dataset:
19
  name: Zeroth Korean
20
  type: kresnik/zeroth_korean
21
  args: clean
22
  metrics:
23
+ - type: wer
 
24
  value: 29.54
25
+ name: Test WER
26
+ - type: cer
27
  value: 9.53
28
+ name: Test CER
29
  - task:
 
30
  type: automatic-speech-recognition
31
+ name: Automatic Speech Recognition
32
  dataset:
33
  name: Robust Speech Event - Dev Data
34
  type: speech-recognition-community-v2/dev_data
35
  args: ko
36
  metrics:
37
+ - type: wer
 
38
  value: 76.26
39
+ name: Test WER
40
+ - type: cer
41
  value: 38.67
42
+ name: Test CER
43
  - task:
 
44
  type: automatic-speech-recognition
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+ name: Automatic Speech Recognition
46
  dataset:
47
  name: Robust Speech Event - Test Data
48
  type: speech-recognition-community-v2/eval_data
49
  args: ko
50
  metrics:
51
+ - 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