osiria
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deberta-italian-question-answering

Question Answering

Inference Endpoints

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osiria commited on Dec 9, 2023

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@@ -78,7 +78,7 @@ Testing notebook: https://huggingface.co/osiria/deberta-italian-question-answeri
 The 3.0 version, with the nickname LITEQA, further improves the performances by exploiting a 3-phases fine-tuning strategy: the model is first fine-tuned on the English SQuAD v2 (1 epoch, 20% warmup ratio, and max learning rate of 3e-5) then further fine-tuned on the Italian SQuAD (2 epochs, no warmup, initial learning rate of 3e-5) and lastly fine-tuned on the lowercase Italian SQuAD (1 epoch, no warmup, initial learning rate of 3e-5).
 This helps making the model generally more robust, but particularly in uncased settings.
-The 3.0 version can be downloaded from the <b>liteqa</b> branch of this repo
 The performances on the test set are reported in the following table:
 (<b>version 3.0</b> performances)

 The 3.0 version, with the nickname LITEQA, further improves the performances by exploiting a 3-phases fine-tuning strategy: the model is first fine-tuned on the English SQuAD v2 (1 epoch, 20% warmup ratio, and max learning rate of 3e-5) then further fine-tuned on the Italian SQuAD (2 epochs, no warmup, initial learning rate of 3e-5) and lastly fine-tuned on the lowercase Italian SQuAD (1 epoch, no warmup, initial learning rate of 3e-5).
 This helps making the model generally more robust, but particularly in uncased settings.
+The 3.0 version can be downloaded from the <b>liteqa</b> branch of this repo.
 The performances on the test set are reported in the following table:
 (<b>version 3.0</b> performances)