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bert-base-uncased-sst2-unstructured80-PTQ – AI Model by yujiepan | AlphaNeural AI
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yujiepan
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bert-base-uncased-sst2-unstructured80-PTQ
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transformers
pytorch
openvino
bert
generated_from_trainer
en
glue
apache-2.0
endpoints_compatible
us
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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
