Model Card for answer-finder-v1-S-en

This model is a question answering model developed by Sinequa. It produces two lists of logit scores corresponding to the start token and end token of an answer.

Model name: answer-finder-v1-S-en

Supported Languages

The model was trained and tested in the following languages:

• English

Scores

Metric	Value
F1 Score on SQuAD v2 with Hugging Face evaluation pipeline	79.4
F1 Score on SQuAD v2 with Haystack evaluation pipeline	79.5

Inference Time

GPU	Quantization type	Batch size 1	Batch size 32
NVIDIA A10	FP16	1 ms	10 ms
NVIDIA A10	FP32	3 ms	43 ms
NVIDIA T4	FP16	2 ms	22 ms
NVIDIA T4	FP32	5 ms	130 ms
NVIDIA L4	FP16	2 ms	12 ms
NVIDIA L4	FP32	5 ms	62 ms

Note that the Answer Finder models are only used at query time.

Gpu Memory usage

Quantization type	Memory
FP16	300 MiB
FP32	550 MiB

Note that GPU memory usage only includes how much GPU memory the actual model consumes on an NVIDIA T4 GPU with a batch size of 32. It does not include the fix amount of memory that is consumed by the ONNX Runtime upon initialization which can be around 0.5 to 1 GiB depending on the used GPU.

Requirements

• Minimal Sinequa version: 11.10.0
• Minimal Sinequa version for using FP16 models and GPUs with CUDA compute capability of 8.9+ (like NVIDIA L4): 11.11.0
• Cuda compute capability: above 5.0 (above 6.0 for FP16 use)

Model Details

Overview

• Number of parameters: 33 million
• Base language model: microsoft/MiniLM-L12-H384-uncased
• Insensitive to casing and accents

Training Data

• SQuAD v2