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bert-base-uncased-sst2-PTQ
yujiepan/bert-base-uncased-sst2-PTQ
bert-base-uncased-sst2-PTQ is a machine learning model from yujiepan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Feb 9, 2023
- Updated
- Feb 9, 2023
- SHA
- 64748db8
Datasets
Model card
From the Hugging Face model README
<!-- 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-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
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Feb 9, 2023
- Updated
- Feb 9, 2023