orai-nlp
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bert-medium-sw

Feature Extraction

Inference Endpoints

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GorkaUrbizu commited on May 31, 2023

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@@ -8,7 +8,7 @@ language:
 BERT medium (cased) model trained on a subset of 125M tokens of cc100-Swahili for our work [Scaling Laws for BERT in Low-Resource Settings]() at ACL2023 Findings.
 The model has 51M parameters (8L), and a vocab size of 50K.
-It was trained for 500K steps with a sequence length of 512 tokens.
 Results
 -----------

 BERT medium (cased) model trained on a subset of 125M tokens of cc100-Swahili for our work [Scaling Laws for BERT in Low-Resource Settings]() at ACL2023 Findings.
 The model has 51M parameters (8L), and a vocab size of 50K.
+It was trained for 500K steps with a sequence length of 512 tokens and batch-size of 256.
 Results
 -----------