| If you use the model, please consider citing the paper | |
| ``` | |
| @misc{bhargava2021generalization, | |
| title={Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics}, | |
| author={Prajjwal Bhargava and Aleksandr Drozd and Anna Rogers}, | |
| year={2021}, | |
| eprint={2110.01518}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| ``` | |
| Original Implementation and more info can be found in [this Github repository](https://github.com/prajjwal1/generalize_lm_nli). | |
| Roberta-large trained on MNLI. | |
| ---------------------- | |
| | Task | Accuracy | | |
| |---------|----------| | |
| | MNLI | 90.15 | | |
| | MNLI-mm | 90.02 | | |
| You can also check out: | |
| - `prajjwal1/roberta-base-mnli` | |
| - `prajjwal1/roberta-large-mnli` | |
| - `prajjwal1/albert-base-v2-mnli` | |
| - `prajjwal1/albert-base-v1-mnli` | |
| - `prajjwal1/albert-large-v2-mnli` | |
| [@prajjwal_1](https://twitter.com/prajjwal_1) | |