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--- |
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license: mit |
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language: |
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- pt |
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model-index: |
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- name: bert-tv-portuguese |
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results: [] |
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--- |
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# BERT-TV |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6385e26cc12615765caa6afe/3lSkNEfW57BNudZIFyTH2.png" width=400 height=400> |
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Image generated by ChatGPT with DALL-E from OpenAI. |
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## Model description |
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BERT-TV is a BERT model specifically pre-trained from scratch on a dataset of television reviews in Brazilian Portuguese. |
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This model is tailored to grasp the nuances and specificities associated with the context and sentiment expressed in |
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television reviews. BERT-TV features 6 layers, 12 attention heads, and an embedding dimension of 768, making it adept at |
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handling NLP tasks related to television content in Portuguese. |
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## Usage ideas |
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- Sentiment analysis on television reviews in Portuguese |
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- Recommender systems for television models in Portuguese |
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- Text classification for different television brands and types in Portuguese |
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- Named entity recognition in television-related contexts in Portuguese |
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- Aspect extraction for features and specifications of televisions in Portuguese |
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- Text generation for summarizing television reviews in Portuguese |
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## Limitations and bias |
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As the BERT-TV model is exclusively pre-trained on television reviews in Brazilian Portuguese, its performance may be |
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limited when applied to other types of text or reviews in different languages. Furthermore, the model could inherit |
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biases present in the training data, which may influence its predictions or embeddings. The tokenizer is adapted from |
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the BERTimbau tokenizer, optimized for Brazilian Portuguese, thus it might not deliver optimal results with other |
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languages or Portuguese dialects. |
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## Framework versions |
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- Transformers 4.27.3 |
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- TensorFlow 2.11.1 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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