DeBERTa-v3-base MultiSpanQA (SpanQualifier Fine-Tuning)
Model Description
This repository contains fine-tuned weights (pytorch_model.bin
) for microsoft/deberta-v3-base
, optimized for multi-span question answering using the SpanQualifier framework.
The model is trained on the MultiSpanQA dataset and is able to predict multiple non-contiguous answer spans from a single context.
โ ๏ธ Important: Only the model weights are provided.
To use this model, load the tokenizer and configuration frommicrosoft/deberta-v3-base
.
Intended Uses
- Use case: Extractive multi-span question answering (e.g., extracting multiple symptoms, medications, goals from text).
- Not for: Free-form text generation or reasoning beyond the given context.
Training Setup
Setting | Value |
---|---|
Base Model | microsoft/deberta-v3-base |
Framework | SpanQualifier |
Dataset | MultiSpanQA (train.json , valid.json ) |
Max Seq Length | 512 |
Learning Rate | 3e-5 |
Batch Size | 32 (gradient accumulation 4) |
Epochs | 20 |
Seed | 30 |
Evaluation Results (MultiSpanQA)
Metric | Precision | Recall | F1 |
---|---|---|---|
Exact Match (EM) | 76.56 | 73.31 | 74.90 |
Partial Match (PM) | 88.49 | 83.37 | 85.86 |
EM = strict span match. PM = overlap-based F1 (gives partial credit).
Example
You can run inference with the provided inference_spanqualifier_hf.py
script.
question = "Who sang it's my party and i'll cry if i want to in the eighties?"
context = (
"In 1981, a remake by British artists Dave Stewart and Barbara Gaskin "
"was a UK number one hit single for four weeks and was also a major hit "
"in Austria (#3), Germany (#3), the Netherlands (#20), New Zealand (#1), "
"South Africa (#3) and Switzerland (#6). The track reached #72 in the US. "
"This was the first version of the song to reach #1 in the UK. The video "
"for the Stewart/Gaskin version contained a cameo by Thomas Dolby as Johnny, "
"Judy being played by Gaskin in a blond wig."
)
Expected model output:
- Dave Stewart
- Barbara Gaskin
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Base model
microsoft/deberta-v3-base