readme: ---
  language: en
  datasets:
  - yelp_polarity
  ---
  
  # RoBERTa-base-finetuned-yelp-polarity
  
  This is a [RoBERTa-base](https://huggingface.co/roberta-base) checkpoint fine-tuned on binary sentiment classifcation from [Yelp polarity](https://huggingface.co/nlp/viewer/?dataset=yelp_polarity).
  It gets **98.08%** accuracy on the test set.
  
  ## Hyper-parameters
  
  We used the following hyper-parameters to train the model on one GPU:
  ```python
  num_train_epochs            = 2.0
  learning_rate               = 1e-05
  weight_decay                = 0.0
  adam_epsilon                = 1e-08
  max_grad_norm               = 1.0
  per_device_train_batch_size = 32
  gradient_accumulation_steps = 1
  warmup_steps                = 3500
  seed                        = 42
  ```
  