Librarian Bot: Add base_model information to model

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  1. README.md +19 -19
README.md CHANGED
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  ---
 
 
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  tags:
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- - text
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- - stance
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- - text-classification
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-
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  pipeline_tag: text-classification
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-
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- language:
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- - en
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-
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  widget:
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- - text: user Bolsonaro is the president of Brazil. He speaks for all brazilians. Greta is a climate activist. Their opinions do create a balance that the world needs now
 
 
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  example_title: example 1
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- - text: user The fact is that she still doesn’t change her ways and still stays non environmental friendly
 
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  example_title: example 2
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  - text: user The criteria for these awards dont seem to be very high.
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  example_title: example 3
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-
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  model-index:
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  - name: Stance-Tw
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  results:
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  - task:
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- type: stance-classification # Required. Example: automatic-speech-recognition
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- name: Text Classification # Optional. Example: Speech Recognition
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  dataset:
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- type: stance # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: stance # Required. A pretty name for the dataset. Example: Common Voice (French)
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  metrics:
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- - type: f1
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- value: 75.8
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- - type: accuracy
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- value: 76.2
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  ---
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  <!-- This model card has been generated automatically according to the information Keras had access to. You should
 
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  ---
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+ language:
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+ - en
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  tags:
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+ - text
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+ - stance
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+ - text-classification
 
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  pipeline_tag: text-classification
 
 
 
 
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  widget:
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+ - text: user Bolsonaro is the president of Brazil. He speaks for all brazilians. Greta
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+ is a climate activist. Their opinions do create a balance that the world needs
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+ now
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  example_title: example 1
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+ - text: user The fact is that she still doesn’t change her ways and still stays non
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+ environmental friendly
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  example_title: example 2
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  - text: user The criteria for these awards dont seem to be very high.
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  example_title: example 3
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+ base_model: j-hartmann/sentiment-roberta-large-english-3-classes
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  model-index:
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  - name: Stance-Tw
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  results:
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  - task:
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+ type: stance-classification
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+ name: Text Classification
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  dataset:
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+ name: stance
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+ type: stance
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  metrics:
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+ - type: f1
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+ value: 75.8
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+ - type: accuracy
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+ value: 76.2
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  ---
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  <!-- This model card has been generated automatically according to the information Keras had access to. You should