Z-Jafari/deduplicated_PersianQuAD
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How to use Z-Jafari/bert-fa-base-uncased-finetuned-deduplicate_PersianQuAD 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-deduplicate_PersianQuAD") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-deduplicate_PersianQuAD")
model = AutoModelForQuestionAnswering.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-deduplicate_PersianQuAD", device_map="auto")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 |
|---|---|---|---|
| 1.1015 | 1.0 | 1285 | 1.0416 |
| 0.6393 | 2.0 | 2570 | 1.0764 |
| 0.4074 | 3.0 | 3855 | 1.2408 |
Base model
HooshvareLab/bert-fa-base-uncased