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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 [`distilbert-base-uncased`](https://huggingface.co/distilbert-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 was requested via the [Librarian Bot](https://huggingface.co/librarian-bot) [metadata request service](https://huggingface.co/spaces/librarian-bots/metadata_request_service) by request of [davanstrien](https://huggingface.co/davanstrien)

Files changed (1) hide show
  1. README.md +4 -3
README.md CHANGED
@@ -6,12 +6,13 @@ datasets:
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  - clinc_oos
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  metrics:
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  - accuracy
 
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  model-index:
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  - name: distilbert-base-uncased-finetuned-clinc
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  results:
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  - task:
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- name: Text Classification
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  type: text-classification
 
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  dataset:
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  name: clinc_oos
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  type: clinc_oos
@@ -19,9 +20,9 @@ model-index:
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  split: train
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  args: plus
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.9161290322580645
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  - clinc_oos
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  metrics:
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  - accuracy
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+ base_model: distilbert-base-uncased
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  model-index:
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  - name: distilbert-base-uncased-finetuned-clinc
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  results:
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  - task:
 
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  type: text-classification
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+ name: Text Classification
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  dataset:
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  name: clinc_oos
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  type: clinc_oos
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  split: train
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  args: plus
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  metrics:
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+ - type: accuracy
 
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  value: 0.9161290322580645
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+ name: Accuracy
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You