Model Card for Model ID

This is a Language Model trained with regional tweets from Mexico using MLM.

Model Details

Model Description

The model use the Roberta architecture. It was trained from random weights using like 110 million tweets from Mexico with an aditional label indicating the State from procedence.

The tweets had the following structure:

STATE _GEO text_from_tweet

The users and url's from the text were replaced by the tokens _USR and _URL respectively.

Developed by: INFOTEC
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Model type: Roberta
Language(s) (NLP): Spanish
License: MIT

Model Sources [optional]

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Uses

The model is intended to be used to extract regional information from Mexico.

Direct Use

The masked token can be used to predict the region of the text. Additionaly, the mask prediction can be used for Information Retrival.

Downstream Use [optional]

The model can be fine-tuned to be used in tasks like Sentiment Analisys, Classification,

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

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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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Software

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Citation [optional]

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