# ishan /distilbert-base-uncased-mnli

system
 1 --- 2 language: en 3 thumbnail:  4 tags: 5 - pytorch 6 - text-classification 7 datasets: 8 - MNLI 9 --- 10 11 # distilbert-base-uncased finetuned on MNLI 12 13 ## Model Details and Training Data 14 15 We used the pretrained model from [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) and finetuned it on [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/) dataset.  16 17 The training parameters were kept the same as [Devlin et al., 2019](https://arxiv.org/abs/1810.04805) (learning rate = 2e-5, training epochs = 3, max_sequence_len = 128 and batch_size = 32). 18 19 ## Evaluation Results 20 21 The evaluation results are mentioned in the table below. 22 23 | Test Corpus | Accuracy | 24 |:---:|:---------:| 25 | Matched | 0.8223 | 26 | Mismatched | 0.8216 | 27 28