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srl-en_mbert-base

Feature Extraction

bert-base-multilingual-cased

semantic role labeling

Inference Endpoints

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sofiaoliveira commited on Jan 12, 2021

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@@ -59,15 +59,9 @@ To use the full SRL model (transformers portion + a decoding layer), refer to th
 - The models were trained only for 5 epochs.
 - The English data was preprocessed to match the Portuguese data, so there are some differences in role attributions and some roles were removed from the data.
-## Training data
-Pretrained weights were left identical to the original model [`bert-base-multilingual-cased`](https://huggingface.co/bert-base-multilingual-cased).
 ## Training procedure
-The models were trained on the CoNLL-2012 dataset, preprocessed to match the Portuguese PropBank.Br data. They were tested on the PropBank.Br data set as well as on a smaller opinion dataset "Buscapé". For more information, please see the accompanying article (See BibTeX entry and citation info below) and the [project's github](https://github.com/asofiaoliveira/srl_bert_pt).
 ## Eval results

 - The models were trained only for 5 epochs.
 - The English data was preprocessed to match the Portuguese data, so there are some differences in role attributions and some roles were removed from the data.
 ## Training procedure
+The model was trained on the CoNLL-2012 dataset, preprocessed to match the Portuguese PropBank.Br data. They were tested on the PropBank.Br data set as well as on a smaller opinion dataset "Buscapé". For more information, please see the accompanying article (See BibTeX entry and citation info below) and the [project's github](https://github.com/asofiaoliveira/srl_bert_pt).
 ## Eval results