Intel/bert-base-uncased-mrpc-int8-qat-inc

INT8 BERT base uncased finetuned MRPC

QuantizationAwareTraining

This is an INT8 PyTorch model quantized with huggingface/optimum-intel through the usage of Intel® Neural Compressor.

The original fp32 model comes from the fine-tuned model Intel/bert-base-uncased-mrpc.

Test result

	INT8	FP32
Accuracy (eval-f1)	0.9142	0.9042
Model size (MB)	107	418

Load with optimum:

from optimum.intel import INCModelForSequenceClassification

model_id = "Intel/bert-base-uncased-mrpc-int8-qat"
int8_model = INCModelForSequenceClassification.from_pretrained(model_id)

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1.0
• train_batch_size: 8
• eval_batch_size: 8
• eval_steps: 100
• load_best_model_at_end: True
• metric_for_best_model: f1
• early_stopping_patience = 6
• early_stopping_threshold = 0.001