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 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 --- 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 |