|
--- |
|
language: en |
|
license: mit |
|
tags: |
|
- text-classfication |
|
- int8 |
|
- Intel® Neural Compressor |
|
- PostTrainingStatic |
|
datasets: |
|
- mrpc |
|
metrics: |
|
- f1 |
|
--- |
|
|
|
# INT8 MiniLM-L12-H384 finetuned MRPC |
|
|
|
## Post-training static quantization |
|
|
|
### PyTorch |
|
|
|
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 [Intel/MiniLM-L12-H384-uncased-mrpc](https://huggingface.co/Intel/MiniLM-L12-H384-uncased-mrpc). |
|
|
|
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. |
|
|
|
The linear module **bert.encoder.layer.6.attention.self.key** falls back to fp32 to meet the 1% relative accuracy loss. |
|
|
|
#### Test result |
|
|
|
| |INT8|FP32| |
|
|---|:---:|:---:| |
|
| **Accuracy (eval-f1)** |0.9039|0.9097| |
|
| **Model size (MB)** |33.5|127| |
|
|
|
#### Load with optimum: |
|
|
|
```python |
|
from optimum.intel import INCModelForSequenceClassification |
|
|
|
model_id = "Intel/MiniLM-L12-H384-uncased-mrpc-int8-static" |
|
int8_model = INCModelForSequenceClassification.from_pretrained(model_id) |
|
``` |
|
|
|
### ONNX |
|
|
|
This is an INT8 ONNX model quantized with [Intel® Neural Compressor](https://github.com/intel/neural-compressor). |
|
|
|
The original fp32 model comes from the fine-tuned model [Intel/MiniLM-L12-H384-uncased-mrpc](https://huggingface.co/Intel/MiniLM-L12-H384-uncased-mrpc). |
|
|
|
The calibration dataloader is the eval dataloader. The calibration sampling size is 100. |
|
|
|
#### Test result |
|
|
|
| |INT8|FP32| |
|
|---|:---:|:---:| |
|
| **Accuracy (eval-f1)** |0.9013|0.9097| |
|
| **Model size (MB)** |33|128| |
|
|
|
|
|
#### Load ONNX model: |
|
|
|
```python |
|
from optimum.onnxruntime import ORTModelForSequenceClassification |
|
model = ORTModelForSequenceClassification.from_pretrained('Intel/MiniLM-L12-H384-uncased-mrpc-int8-static') |
|
``` |
|
|
