| license: apache-2.0 | |
| tags: | |
| - int8 | |
| - Intel® Neural Compressor | |
| - PostTrainingStatic | |
| datasets: | |
| - squad | |
| metrics: | |
| - f1 | |
| # INT8 DistilBERT base cased finetuned on Squad | |
| ### Post-training static quantization | |
| This is an INT8 PyTorch model quantized with [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [Intel® Neural Compressor](https://github.com/intel/neural-compressor). | |
| The original fp32 model comes from the fine-tuned model [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad). | |
| 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. | |
| The linear module **distilbert.transformer.layer.1.ffn.lin2** falls back to fp32 to meet the 1% relative accuracy loss. | |
| ### Test result | |
| | |INT8|FP32| | |
| |---|:---:|:---:| | |
| | **Accuracy (eval-f1)** |86.0005|86.8373| | |
| | **Model size (MB)** |71.2|249| | |
| ### Load with optimum: | |
| ```python | |
| from optimum.intel import INCModelForQuestionAnswering | |
| model_id = "Intel/distilbert-base-cased-distilled-squad-int8-static" | |
| int8_model = INCModelForQuestionAnswering.from_pretrained(model_id) | |
| ``` | |