Cross Lingual Natural Language Inference On 4
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| Coupled | 70.7 | Rethinking embedding coupling in pre-trained language models | |
| Decoupled | 71.3 | Rethinking embedding coupling in pre-trained language models | |
| ByT5 Small | 69.1 | ByT5: Towards a token-free future with pre-trained byte-to-byte models | |
| mGPT | 40.6 | mGPT: Few-Shot Learners Go Multilingual | |
| ByT5 XXL | 83.7 | ByT5: Towards a token-free future with pre-trained byte-to-byte models |
0 of 5 row(s) selected.