Sparse BERT base model fine tuned to MNLI without classifier layer (uncased)

Fine tuned sparse BERT base to MNLI (GLUE Benchmark) task from bert-base-uncased-sparse-70-unstructured.
This model doesn't have a classifier layer to enable easier loading of the model for training to other downstream tasks. In all the other layers this model is similar to bert-base-uncased-mnli-sparse-70-unstructured.

Note: This model requires transformers==2.10.0

Evaluation Results

Matched: 82.5%
Mismatched: 83.3%

This model can be further fine-tuned to other tasks and achieve the following evaluation results:

Task QQP (Acc/F1) QNLI (Acc) SST-2 (Acc) STS-B (Pears/Spear) SQuADv1.1 (Acc/F1)
90.2/86.7 90.3 91.5 88.9/88.6 80.5/88.2
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This model can be loaded on the Inference API on-demand.