text: [BERT]
  model_name_or_path="bert-base-cased"
  task_name="fevercrossdomain"
  do_train=True
  do_eval=True
  do_predict=True
  do_train_1student_1teacher=True
  data_dir="/Users/mordor/research/huggingface/src/transformers/data/datasets/fever/fevercrossdomain/combined/figerspecific/toydata/"
  max_seq_length="128"
  per_device_eval_batch_size="16"
  per_device_train_batch_size="16"
  learning_rate="1e-5"
  # Note: use num_train_epochs=1 only. For testing purposes, in trainery.py we are as of now, sep 2020 we are returning the dev and test partition evaluation results for epoch1
  # if you want to test for more than 1 eopch, return best_dev and best_test values
  num_train_epochs="1"
  output_dir="/Users/mordor/research/huggingface/mithun_scripts/output/fever/fevercrossdomain/combined/figerspecific/bert-base-cased/128/"
  overwrite_output_dir=True
  weight_decay="0.01"
  adam_epsilon="1e-6"
  evaluate_during_training=True
  task_type="combined"
  subtask_type="figerspecific"
  machine_to_run_on="laptop"
  toy_data_dir_path="/Users/mordor/research/huggingface/src/transformers/data/datasets/fever/fevercrossdomain/combined/figerspecific/toydata/"
  #what are the scores that you should assert against. i.e the ones we got when we ran the toy data alone
  fever_in_domain_accuracy_on_toy_data_17_datapoints=0.5625
  fever_cross_domain_accuracy_on_toy_data_17_datapoints=0.75
  fever_cross_domain_fncscore_on_toy_data_17_datapoints=0.8