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
- Downloads last month
- 31
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.