readme: <<<<<<< HEAD
  ---
  tags:
  - generated_from_trainer
  datasets:
  - financial_phrasebank
  model-index:
  - name: test_trainer_1
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # test_trainer_1
  
  This model is a fine-tuned version of [SALT-NLP/FLANG-Roberta](https://huggingface.co/SALT-NLP/FLANG-Roberta) on the financial_phrasebank dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.5963
  - eval_accuracy: 0.9242
  - eval_runtime: 4.3354
  - eval_samples_per_second: 97.337
  - eval_steps_per_second: 12.225
  - step: 0
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  =======
  This is a demo model for our reference
  >>>>>>> 24191373ff05e3799b9c6f359e51b37b642f4865
  