Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`t5-small`](https://huggingface.co/t5-small) 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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metrics:
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- Dialog acts Accuracy
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- Dialog acts F1
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model-index:
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- name: t5-small-nlu-sgd
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results:
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type: text2text-generation
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name: natural language understanding
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dataset:
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type: ConvLab/sgd
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name: SGD
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split: test
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revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f
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metrics:
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widget:
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- text: "user: Could you get me a reservation at P.f. Chang's in Corte Madera at afternoon 12?"
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- text: "user: Sure, may I know if they have vegetarian options and how expensive is their food?"
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inference:
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parameters:
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max_length: 100
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---
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# t5-small-nlu-sgd
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metrics:
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- Dialog acts Accuracy
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- Dialog acts F1
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widget:
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- text: 'user: Could you get me a reservation at P.f. Chang''s in Corte Madera at
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afternoon 12?'
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- text: 'user: Sure, may I know if they have vegetarian options and how expensive
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is their food?'
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inference:
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parameters:
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max_length: 100
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base_model: t5-small
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model-index:
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- name: t5-small-nlu-sgd
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results:
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type: text2text-generation
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name: natural language understanding
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dataset:
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name: SGD
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type: ConvLab/sgd
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split: test
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revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f
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metrics:
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- type: Dialog acts Accuracy
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value: 45.0
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name: Accuracy
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- type: Dialog acts F1
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value: 58.6
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name: F1
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---
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# t5-small-nlu-sgd
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