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Model Description

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  • Developed by: Adrián Ghajari, Salvador Ros, Víctor Fresno, Alejandro Benito, Elena González-Blanco.
  • Funded by: LyrAIcs Grant agreement ID: 964009 H2020 EXCELLENCE SCIENCE- European Research Council
  • Model type: Bert
  • Language(s) (NLP): Multilingual
  • Finetuned from model [optional]: alberti-bert-base-multilingual-cased

Model Sources [optional]

  • Paper: pending

Uses

Model trained with a song lyrics dataset. The dataset was divided into chunks. This model is designed to create embeddings of song lyrics.

Direct Use

Creation of embeddings through semantic composition

Downstream Use

Lyrics Similarity

Training Details

Training Data

LyrAIcs dataset

Training Procedure

Preprocessing

Chunking

Training Hyperparameters

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Speeds, Sizes, Times [optional]

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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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