yujiepan/bert-base-uncased-sst2-PTQ

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bert-base-uncased-sst2-PTQ

This model conducts simple post training quantization of textattack/bert-base-uncased-SST-2 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

• —torch loss: 0.2140
• —torch accuracy: 0.9243
• —OpenVINO IR accuracy: 0.9174

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: 1e-05
• —trainbatchsize: 32
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 3.0

Framework versions

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