metadata
language: en
license: apache-2.0
tags:
- text-classfication
- int8
- PostTrainingStatic
datasets:
- sst2
metrics:
- accuracy
INT8 DistilBERT base uncased finetuned SST-2
Post-training static quantization
This is an INT8 PyTorch model quantized with Intel® Neural Compressor.
The original fp32 model comes from the fine-tuned model distilbert-base-uncased-finetuned-sst-2-english.
The calibration dataloader is the train dataloader. The default calibration sampling size 100 isn't divisible exactly by batch size 8, so the real sampling size is 104.
Test result
INT8 | FP32 | |
---|---|---|
Accuracy (eval-accuracy) | 0.9037 | 0.9106 |
Model size (MB) | 65 | 255 |
Load with Intel® Neural Compressor (build from source):
from neural_compressor.utils.load_huggingface import OptimizedModel
int8_model = OptimizedModel.from_pretrained(
'Intel/distilbert-base-uncased-finetuned-sst-2-english-int8-static',
)