--- language: en license: mit tags: - text-classfication - int8 - IntelĀ® Neural Compressor - QuantizationAwareTraining datasets: - mrpc metrics: - f1 --- # INT8 MiniLM finetuned MRPC ### QuantizationAwareTraining This is an INT8 PyTorch model quantized with [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [IntelĀ® 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). ### Test result | |INT8|FP32| |---|:---:|:---:| | **Accuracy (eval-f1)** |0.9068|0.9097| | **Model size (MB)** |33.1|127| ### Load with optimum: ```python from optimum.intel import INCModelForSequenceClassification model_id = "Intel/MiniLM-L12-H384-uncased-mrpc-int8-qat" int8_model = INCModelForSequenceClassification(model_id) ``` ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1.0 - train_batch_size: 16 - eval_batch_size: 8