Z-Jafari/PersianQuAD
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How to use Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-3epochs with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-3epochs") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-3epochs")
model = AutoModelForQuestionAnswering.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-3epochs")This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7542 | 1.0 | 2263 | 0.9798 |
| 0.4534 | 2.0 | 4526 | 1.1048 |
| 0.2673 | 3.0 | 6789 | 1.2590 |
Base model
HooshvareLab/bert-fa-base-uncased