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metadata
datasets: dvquys/restaurant-reviews-public-sources
language: en
library_name: pytorch
license: mit
tags:
  - ner
  - reviews
  - fine-tune
  - token classification

Model Card for ner-finetune-restaurant-reviews-aspects

Model Details

Model Description

Reviews Parsing NER Aspects

This model takes a text review as input and output the parsed aspects mentioned which spans over the entity and the sentiment text.

It's based on the idea of fine-tuning a base LLM with a token classification task.

More info: https://huggingface.co/learn/nlp-course/en/chapter7/2#token-classification

  • Developed by: Quy Dinh
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  • Model type: [More Information Needed]
  • Language(s) (NLP): en
  • License: mit
  • Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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