Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`openai/whisper-large-v2`](https://huggingface.co/openai/whisper-large-v2) 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: fr
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library_name: transformers
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thumbnail: null
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tags:
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- automatic-speech-recognition
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- hf-asr-leaderboard
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- gigant/african_accented_french
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metrics:
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- wer
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model-index:
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- name: Fine-tuned whisper-large-v2 model for ASR in French
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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: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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split: test
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args: fr
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metrics:
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-
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type: wer
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value: 8.15
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value: 7.83
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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: Multilingual LibriSpeech (MLS)
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type: facebook/multilingual_librispeech
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split: test
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args: french
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metrics:
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type: wer
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value: 4.03
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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: VoxPopuli
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type: facebook/voxpopuli
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@@ -60,15 +60,15 @@ model-index:
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split: test
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args: fr
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metrics:
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-
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type: wer
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value: 8.66
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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: Fleurs
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type: google/fleurs
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split: test
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args: fr_fr
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metrics:
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-
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type: wer
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value: 5.22
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-
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-
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value: 4.98
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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: African Accented French
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type: gigant/african_accented_french
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split: test
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args: fr
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metrics:
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-
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type: wer
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value: 4.58
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value: 4.31
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---
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<style>
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---
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language: fr
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license: apache-2.0
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library_name: transformers
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tags:
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- automatic-speech-recognition
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- hf-asr-leaderboard
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- gigant/african_accented_french
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metrics:
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- wer
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base_model: openai/whisper-large-v2
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model-index:
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- name: Fine-tuned whisper-large-v2 model for ASR in French
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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: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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split: test
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args: fr
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metrics:
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- type: wer
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value: 8.15
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name: WER (Greedy)
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- type: wer
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value: 7.83
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name: WER (Beam 5)
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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: Multilingual LibriSpeech (MLS)
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type: facebook/multilingual_librispeech
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split: test
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args: french
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metrics:
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- type: wer
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value: 4.2
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name: WER (Greedy)
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- type: wer
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value: 4.03
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name: WER (Beam 5)
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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: VoxPopuli
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type: facebook/voxpopuli
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split: test
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args: fr
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metrics:
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- type: wer
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value: 9.1
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name: WER (Greedy)
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- type: wer
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value: 8.66
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name: WER (Beam 5)
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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: Fleurs
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type: google/fleurs
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split: test
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args: fr_fr
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metrics:
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- type: wer
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value: 5.22
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name: WER (Greedy)
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- type: wer
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value: 4.98
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name: WER (Beam 5)
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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: African Accented French
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type: gigant/african_accented_french
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split: test
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args: fr
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metrics:
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- type: wer
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value: 4.58
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name: WER (Greedy)
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- type: wer
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value: 4.31
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name: WER (Beam 5)
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---
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<style>
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