ema_task_entailment / README.md
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metadata
license: apache-2.0
datasets:
  - nyu-mll/multi_nli
language:
  - en
metrics:
  - accuracy
library_name: adapter-transformers
pipeline_tag: text-classification
tags:
  - code
base_model:
  - sinancavdar/BertForSequenceClassification

Entailment Detection by Fine-tuning BERT


  • The model in this repository is fine-tuned on Google's encoder-decoder transformer-based model BERT.
  • New York University's Multi-NLI dataset is used for fine-tuning.
  • Accuracy achieved: ~74%

    image/png

  • Notebook used for fine-tuning: here
  • N.B.: Due to computational resource constraints, only 11K samples are used for fine-tuning. There is room for accuracy improvement if a model is trained on all the 390K samples available in the dataset.