wiki_all
Collection
6 items • Updated
How to use Z-Jafari/roberta-fa-zwnj-base-finetuned-PersianQuAD-wiki_ds_Scored-all-rows with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Z-Jafari/roberta-fa-zwnj-base-finetuned-PersianQuAD-wiki_ds_Scored-all-rows") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Z-Jafari/roberta-fa-zwnj-base-finetuned-PersianQuAD-wiki_ds_Scored-all-rows")
model = AutoModelForQuestionAnswering.from_pretrained("Z-Jafari/roberta-fa-zwnj-base-finetuned-PersianQuAD-wiki_ds_Scored-all-rows")This model is a fine-tuned version of HooshvareLab/roberta-fa-zwnj-base 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 |
|---|---|---|---|
| 0.8373 | 1.0 | 4094 | 1.4770 |
| 0.5591 | 2.0 | 8188 | 1.4657 |
| 0.3538 | 3.0 | 12282 | 1.6382 |
Base model
HooshvareLab/roberta-fa-zwnj-base