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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 [`google/bert_uncased_L-4_H-256_A-4`](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) 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 +6 -5
README.md CHANGED
@@ -7,12 +7,13 @@ datasets:
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  metrics:
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  - accuracy
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  - f1
 
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  model-index:
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  - name: finetuned-base_mini
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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: imdb
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  type: imdb
@@ -20,12 +21,12 @@ model-index:
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  split: train
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  args: plain_text
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.9076
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- - name: F1
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- type: f1
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  value: 0.9515621723631789
 
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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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  metrics:
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  - accuracy
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  - f1
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+ base_model: google/bert_uncased_L-4_H-256_A-4
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  model-index:
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  - name: finetuned-base_mini
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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: imdb
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  type: imdb
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  split: train
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  args: plain_text
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  metrics:
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+ - type: accuracy
 
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  value: 0.9076
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+ name: Accuracy
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+ - type: f1
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  value: 0.9515621723631789
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+ name: F1
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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