babylm-es

Model Card for Model ID

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Model Details

Model Description

• Developed by: A. Britez
• Model type: RoBERTa
• Language(s) (NLP): ES - Rioplatense Spanish

Model Sources [optional]

• Repository: https://github.com/abrtz/baby-lm

Uses

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Direct Use

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[More Information Needed]

Bias, Risks, and Limitations

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[More Information Needed]

Recommendations

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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

datasets:

• piuba-bigdata/articles_and_comments

Training Procedure

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Preprocessing [optional]

[More Information Needed]

Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

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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

• Hardware Type: A100-SXM4-40GB
• Hours used: 1.2 hours
• Cloud Provider: Google Cloud Platform
• Compute Region: europe-west4
• Carbon Emitted: Total emissions are estimated to be 0.17 kgCO$_2$eq of which 100 percents were directly offset by the cloud provider.

Estimations were conducted using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Technical Specifications [optional]

Model Architecture and Objective

RoBERTa for MLM

Glossary [optional]

BabyLM