metadata
language:
- de
- en
- es
- fr
Model Card for answer-finder-v1-L-multilingual
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-L-multilingual
Supported Languages
The model was trained and tested in the following languages:
- English
- French
- German
- Spanish
Scores
| Metric | Value |
|---|---|
| F1 Score on SQuAD v2 EN with Hugging Face evaluation pipeline | 75 |
| F1 Score on SQuAD v2 EN with Haystack evaluation pipeline | 75 |
| F1 Score on SQuAD v2 FR with Haystack evaluation pipeline | 73.4 |
| F1 Score on SQuAD v2 DE with Haystack evaluation pipeline | 90.8 |
| F1 Score on SQuAD v2 ES with Haystack evaluation pipeline | 67.1 |
Inference Time
| GPU Info | Batch size 1 | Batch size 32 |
|---|---|---|
| NVIDIA A10 | 4 ms | 84 ms |
| NVIDIA T4 | 15 ms | 362 ms |
Note that the Answer Finder models are only used at query time.
Requirements
- Minimal Sinequa version: 11.10.0
- GPU memory usage: 1060 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.
Model Details
Overview
- Number of parameters: 110 million
- Base language model: bert-base-multilingual-cased pre-trained by Sinequa in English, French, German and Spanish
- Insensitive to casing and accents
Training Data
- SQuAD v2
- French-SQuAD + French translation of SQuAD v2 "impossible" query-passage pairs
- GermanQuAD + German translation of SQuAD v2 "impossible" query-passage pairs
- SQuAD-es-v2