bert-base-uncased-sst2-unstructured-sparsity-80
This model is a fine-tuned version of bert-base-uncased on the GLUE SST2 dataset. The sparsity on linear layers is 80%.
It achieves the following results on the evaluation set:
- eval_loss: 0.4133
- eval_accuracy: 0.9128
- eval_runtime: 31.5327
- eval_samples_per_second: 27.654
- eval_steps_per_second: 3.457
Model description
- eval config： max_seq_length 128
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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