---
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

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## Model Details

### Model Description

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# 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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- **Language(s) (NLP):** en
- **License:** mit
- **Finetuned from model [optional]:** [More Information Needed]

### Model Sources [optional]

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- **Repository:** https://github.com/huggingface/huggingface_hub
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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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## How to Get Started with the Model

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## Training Details

### Training Data

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### Training Procedure

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#### Training Hyperparameters

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## Evaluation

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### Results

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#### Summary



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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

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## Citation [optional]

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