Update config.json
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config.json
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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---
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language: es
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tags:
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• sentiment-analysis
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• text-classification
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• spanish
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• xlm-roberta
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datasets:
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• custom # Reemplaza esto con el nombre del dataset si es público
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metrics:
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• accuracy
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• f1
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license: mit # Ajusta esto según la licencia de tu modelo
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model-index:
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• name: bert-bregman
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results:
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- task:
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type: text-classification
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name: Sentiment Analysis
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dataset:
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name: Custom Spanish Sentiment Dataset
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type: custom # Ajusta esto si usaste un dataset público
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metrics:
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- type: accuracy
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value: 0.7432432432432432
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- type: f1
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value: 0.7330748170322471
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pipeline_tag: text-classification
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widget:
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- text: "Me encanta este producto, es excelente!"
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example_title: "Ejemplo positivo"
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- text: "No estoy seguro si me gusta o no."
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example_title: "Ejemplo neutro"
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- text: "Este servicio es terrible, nunca lo recomendaría."
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example_title: "Ejemplo negativo"
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---
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