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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 [`bert-base-uncased`](https://huggingface.co/bert-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 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!

Files changed (1) hide show
  1. README.md +16 -15
README.md CHANGED
@@ -7,20 +7,21 @@ datasets:
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  - amazon_polarity
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  metrics:
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  - accuracy
 
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  model-index:
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  - name: bert-base-uncased-amazon_polarity
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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: amazon_polarity
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  type: amazon_polarity
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  args: amazon_polarity
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.94647
 
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  - task:
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  type: text-classification
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  name: Text Classification
@@ -30,29 +31,29 @@ model-index:
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  config: amazon_polarity
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  split: test
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.9464875
 
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  verified: true
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- - name: Precision
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- type: precision
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  value: 0.9528844934702675
 
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  verified: true
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- - name: Recall
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- type: recall
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  value: 0.939425
 
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  verified: true
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- - name: AUC
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- type: auc
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  value: 0.9863499156250001
 
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  verified: true
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- - name: F1
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- type: f1
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  value: 0.9461068798388619
 
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  verified: true
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- - name: loss
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- type: loss
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  value: 0.2944573760032654
 
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  verified: true
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  ---
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  - amazon_polarity
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  metrics:
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  - accuracy
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+ base_model: bert-base-uncased
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  model-index:
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  - name: bert-base-uncased-amazon_polarity
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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: amazon_polarity
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  type: amazon_polarity
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  args: amazon_polarity
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  metrics:
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+ - type: accuracy
 
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  value: 0.94647
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+ name: Accuracy
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  - task:
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  type: text-classification
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  name: Text Classification
 
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  config: amazon_polarity
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  split: test
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  metrics:
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+ - type: accuracy
 
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  value: 0.9464875
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+ name: Accuracy
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  verified: true
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+ - type: precision
 
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  value: 0.9528844934702675
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+ name: Precision
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  verified: true
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+ - type: recall
 
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  value: 0.939425
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+ name: Recall
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  verified: true
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+ - type: auc
 
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  value: 0.9863499156250001
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+ name: AUC
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  verified: true
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+ - type: f1
 
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  value: 0.9461068798388619
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+ name: F1
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  verified: true
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+ - type: loss
 
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  value: 0.2944573760032654
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+ name: loss
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  verified: true
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  ---
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