FiqhQA
Collection
27 items • Updated
How to use mhdafifan/mdeberta-threestage-fiqhqa-ML-384 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="mhdafifan/mdeberta-threestage-fiqhqa-ML-384") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("mhdafifan/mdeberta-threestage-fiqhqa-ML-384")
model = AutoModelForQuestionAnswering.from_pretrained("mhdafifan/mdeberta-threestage-fiqhqa-ML-384")This model is a fine-tuned version of mhdafifan/mdeberta-squad-qasina-LR-5e-06-BS-16-ML-384 on the FiqhQA 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 | F1 | Exact Match |
|---|---|---|---|---|---|
| 0.9528 | 1.0 | 258 | 0.9152 | 50.65 | 23.3 |
| 0.7986 | 2.0 | 516 | 0.9110 | 51.31 | 25.24 |
| 0.6475 | 3.0 | 774 | 0.9849 | 51.89 | 24.27 |
| 0.5222 | 4.0 | 1032 | 1.0453 | 50.62 | 21.36 |
| 0.3937 | 5.0 | 1290 | 1.1203 | 49.97 | 21.36 |
Base model
microsoft/mdeberta-v3-base