Slovenian RoBERTa contextual embeddings model: SloBERTa 1.0

Name: Slovenian RoBERTa contextual embeddings model: SloBERTa 1.0
License: https://opensource.org/licenses/mit-license.php

Ulčar, Matej; Robnik-Šikonja, Marko

Slovenian RoBERTa contextual embeddings model: SloBERTa 1.0

CLARIN.SI data & tools

Authors: Ulčar, Matej and Robnik-Šikonja, Marko

Item identifier: http://hdl.handle.net/11356/1387

Project URL: https://rsdo.slovenscina.eu/en/semantic-resources-and-technologies

Date issued: 2020-12-29

Type: toolService

Language(s): Slovenian

Description: The monolingual Slovene RoBERTa (A Robustly Optimized Bidirectional Encoder Representations from Transformers) model is a state-of-the-art model representing words/tokens as contextually dependent word embeddings, used for various NLP tasks. Word embeddings can be extracted for every word occurrence and then used in training a model for an end task, but typically the whole RoBERTa model is fine-tuned end-to-end. SloBERTa model is closely related to French Camembert model https://camembert-model.fr/. The corpora used for training the model have 3.47 billion tokens in total. The subword vocabulary contains 32,000 tokens. The scripts and programs used for data preparation and training the model are available on https://github.com/clarinsi/Slovene-BERT-Tool The released model here is a pytorch neural network model, intended for usage with the transformers library https://github.com/huggingface/transformers.

Publisher: Faculty of Computer and Information Science, University of Ljubljana

Subject(s): BERT RoBERTa word embeddings language model contextual embeddings

Collection(s): CLARIN.SI data & tools

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http://hdl.handle.net/11356/1397

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Name: config.json
Size: 520 bytes
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Description: Configuration file, describing the model's architecture
MD5: 00189fa49a298a01e689fafbffff9fb5

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Name: pytorch_model.bin
Size: 422.32 MB
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Description: SloBERTa model
MD5: e84c8114553e35003c8b5777534c8d4a

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Name: sentencepiece.bpe.model
Size: 781.26 KB
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Description: Sentencepiece model tokenizer
MD5: e4acd9c398b3fc68e1b2bc0f27d0d409

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Name: dict.txt
Size: 424.06 KB
Format: Text file
Description: Sentencepiece subword token vocabulary
MD5: c3988aad6b209cf7f61667bbf2aba173

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Slovenian RoBERTa contextual embeddings model: SloBERTa 1.0

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