Model Card for answer-finder.yuzu
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.yuzu
Supported Languages
The model was trained and tested in the following languages:
- Japanese
Besides the aforementioned languages, basic support can be expected for the 104 languages that were used during the pretraining of the base model (See original repository).
Scores
| Metric | Value |
|---|---|
| F1 Score on JSQuAD with Hugging Face evaluation pipeline | 92.1 |
| F1 Score on JSQuAD with Haystack evaluation pipeline | 91.5 |
Inference Time
| GPU | Quantization type | Batch size 1 | Batch size 32 |
|---|---|---|---|
| NVIDIA A10 | FP16 | 17 ms | 27 ms |
| NVIDIA A10 | FP32 | 4 ms | 88 ms |
| NVIDIA T4 | FP16 | 3 ms | 64 ms |
| NVIDIA T4 | FP32 | 15 ms | 374 ms |
| NVIDIA L4 | FP16 | 3 ms | 39 ms |
| NVIDIA L4 | FP32 | 5 ms | 125 ms |
Note that the Answer Finder models are only used at query time.
Gpu Memory usage
| Quantization type | Memory |
|---|---|
| FP16 | 950 MiB |
| FP32 | 1350 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
- Cuda compute capability: above 5.0 (above 6.0 for FP16 use)
Model Details
Overview
- Number of parameters: 110 million
- Base language model: bert-base-multilingual-cased
- Sensitive to casing and accents