bert-base-uncased-sst2-unstructured80-PTQ

This model conducts simple post training quantization of yujiepan/bert-base-uncased-sst2-unstructured-sparsity-80 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

• torch loss: 0.4029
• torch accuracy: 0.9128
• OpenVINO IR accuracy: 0.9117
• Sparsity in transformer block linear layers: 0.80

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 3e-05
• train_batch_size: 64
• eval_batch_size: 8
• seed: 1
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine_with_restarts
• num_epochs: 12.0
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2