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INT8 xlnet-base-cased-mrpc

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 xlnet-base-cased-mrpc.

The calibration dataloader is the train dataloader. The default calibration sampling size 300 isn't divisible exactly by batch size 8, so the real sampling size is 304.

Test result

Accuracy (eval-f1) 0.8893 0.8897
Model size (MB) 215 448

Load with Intel® Neural Compressor:

from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSequenceClassification

int8_model = IncQuantizedModelForSequenceClassification.from_pretrained(
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Dataset used to train Intel/xlnet-base-cased-mrpc-int8-static

Evaluation results