Edit model card

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
Downloads last month
33
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

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