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Fine-tuned LongT5 for Conversational QA (ONNX Format)

This model is an ONNX export of tryolabs/long-t5-tglobal-base-blogpost-cqa, a fine-tuned version of long-t5-tglobal-base for the task of Conversational QA. The model was fine-tuned on the SQuADv2 and CoQA datasets and on Tryolabs' own custom dataset, TryoCoQA.

The model was exported using πŸ€— Optimum's exporters feature, which separates the original model into three componentes: the encoder, the decoder with the Language Modeling head, and the decoder with hidden states as additional inputs. Using πŸ€— Optimum and ONNX Runtime, you can combine these components for faster inference.

You can find the details on how we fine-tuned the model and built TryoCoQA on our blog post!

You can also play with the model on the following space.

Results

  • Fine-tuning for 3 epochs on SQuADv2 and CoQA combined achieved a 74.29 F1 score on the test set.
  • Fine-tuning for 166 epochs on TryoCoQA achieved a 54.77 F1 score on the test set.
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