metadata
language: en
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 |