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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: bert-base-uncased-sst2-unstructured80-PTQ
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-uncased-sst2-unstructured80-PTQ
This model conducts simple post training quantization of [yujiepan/bert-base-uncased-sst2-unstructured-sparsity-80](https://huggingface.co/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
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