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  As part of the ITANONG project's 10 billion-token Tagalog dataset, we have introduced a collection of pre-trained embedding models. These models were trained using the Formal text dataset from the renowned corpus which has been thoroughly detailed in our paper. Details of the embedding models can be seen below:
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- $$
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- \usepackage{multirow}
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- \begin{table}[h]
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- \centering
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- \begin{tabular}{|c|c|c|c|}
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- \hline
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- Embedding Technique & Variant & Model File Format & Embedding Size \\ \hline
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- \multirow{24}{*}{Word2Vec} & \multirow{12}{*}{Skipgram} & \multirow{6}{*}{.bin} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \cline{3-4}
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- & & \multirow{6}{*}{.txt} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \cline{2-4}
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- & \multirow{12}{*}{CBOW} & \multirow{6}{*}{.bin} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \cline{3-4}
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- & & \multirow{6}{*}{.txt} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \hline
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- \multirow{24}{*}{FastText} & \multirow{12}{*}{Skipgram} & \multirow{6}{*}{.bin} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \cline{3-4}
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- & & \multirow{6}{*}{.txt} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \cline{2-4}
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- & \multirow{12}{*}{CBOW} & \multirow{6}{*}{.bin} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \cline{3-4}
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- & & \multirow{6}{*}{.txt} & 20 \\ \cline{4-4}
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- & & & 30 \\ \cline{4-4}
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- & & & 50 \\ \cline{4-4}
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- & & & 100 \\ \cline{4-4}
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- & & & 200 \\ \cline{4-4}
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- & & & 300 \\ \hline
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- \end{tabular}
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- \end{table}
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-
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- $$
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Training Details
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  This model was trained using an Nvidia V100-32GB GPU on DOST-ASTI Computing and Archiving Research Environment (COARE) - https://asti.dost.gov.ph/projects/coare/
 
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  As part of the ITANONG project's 10 billion-token Tagalog dataset, we have introduced a collection of pre-trained embedding models. These models were trained using the Formal text dataset from the renowned corpus which has been thoroughly detailed in our paper. Details of the embedding models can be seen below:
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+ +---------------------+----------+-------------------+----------------+
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+ | Embedding Technique | Variant | Model File Format | Embedding Size |
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+ +---------------------+----------+-------------------+----------------+
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+ | Word2Vec | Skipgram | .bin | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ | | +-------------------+----------------+
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+ | | | .txt | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ | +----------+-------------------+----------------+
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+ | | CBOW | .bin | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ | | +-------------------+----------------+
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+ | | | .txt | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ +---------------------+----------+-------------------+----------------+
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+ | FastText | Skipgram | .bin | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ | | +-------------------+----------------+
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+ | | | .txt | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ | +----------+-------------------+----------------+
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+ | | CBOW | .bin | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ | | +-------------------+----------------+
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+ | | | .txt | 20 |
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+ | | | +----------------+
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+ | | | | 30 |
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+ | | | +----------------+
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+ | | | | 50 |
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+ | | | +----------------+
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+ | | | | 100 |
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+ | | | +----------------+
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+ | | | | 200 |
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+ | | | +----------------+
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+ | | | | 300 |
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+ +---------------------+----------+-------------------+----------------+
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  ## Training Details
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  This model was trained using an Nvidia V100-32GB GPU on DOST-ASTI Computing and Archiving Research Environment (COARE) - https://asti.dost.gov.ph/projects/coare/