readme: ---
  language: en
  thumbnail: 
  tags:
  - pytorch
  - text-classification
  datasets:
  - MNLI
  ---
  
  # distilbert-base-uncased finetuned on MNLI
  
  ## Model Details and Training Data
  
  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. 
  
  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).
  
  ## Evaluation Results
  
  The evaluation results are mentioned in the table below.
  
  | Test Corpus | Accuracy |
  |:---:|:---------:|
  | Matched | 0.8223 |
  | Mismatched | 0.8216 |
  
  