SeyedAli/Persian-Text-QA
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How to use SeyedAli/Persian-QA-Bert-V1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="SeyedAli/Persian-QA-Bert-V1") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("SeyedAli/Persian-QA-Bert-V1")
model = AutoModelForQuestionAnswering.from_pretrained("SeyedAli/Persian-QA-Bert-V1")This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on SeyedAli/Persian-Text-QA 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 |
|---|---|---|---|
| 2.3247 | 1.0 | 1126 | 1.7615 |
| 1.4445 | 2.0 | 2252 | 1.8002 |
| 0.7653 | 3.0 | 3378 | 2.0806 |
| 0.4247 | 4.0 | 4504 | 2.6624 |
| 0.2502 | 5.0 | 5630 | 3.2961 |
| 0.168 | 6.0 | 6756 | 3.7767 |
| 0.0809 | 7.0 | 7882 | 4.3288 |
| 0.0544 | 8.0 | 9008 | 4.8516 |
| 0.0398 | 9.0 | 10134 | 4.9091 |
| 0.0102 | 10.0 | 11260 | 5.0331 |
Base model
HooshvareLab/bert-fa-base-uncased