Z-Jafari/PersianQuAD
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How to use Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-PersianQuAD_Q_DeepseekQA_M_M_QA-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-finetuned-PersianQuAD_Q_DeepseekQA_M_M_QA-3epochs") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-PersianQuAD_Q_DeepseekQA_M_M_QA-3epochs")
model = AutoModelForQuestionAnswering.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-PersianQuAD_Q_DeepseekQA_M_M_QA-3epochs")This model is a fine-tuned version of Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-3epochs 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 |
|---|---|---|---|
| 0.3823 | 1.0 | 2026 | 1.2729 |
| 0.2187 | 2.0 | 4052 | 1.4317 |
| 0.1168 | 3.0 | 6078 | 1.7271 |
Base model
HooshvareLab/bert-fa-base-uncased