readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - financial_phrasebank
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-large-uncased-financial-phrasebank-allagree2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: financial_phrasebank
        type: financial_phrasebank
        config: sentences_allagree
        split: train
        args: sentences_allagree
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9911504424778761
      - name: F1
        type: f1
        value: 0.9910704012566471
  ---
  
  <!-- 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. -->
  
  # bert-large-uncased-financial-phrasebank-allagree2
  
  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the financial_phrasebank dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0734
  - Accuracy: 0.9912
  - F1: 0.9911
  
  ## 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: 2e-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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.3209        | 1.0   | 227  | 0.1929          | 0.9558   | 0.9551 |
  | 0.0821        | 2.0   | 454  | 0.0994          | 0.9867   | 0.9867 |
  | 0.04          | 3.0   | 681  | 0.0685          | 0.9867   | 0.9866 |
  | 0.0098        | 4.0   | 908  | 0.0980          | 0.9867   | 0.9867 |
  | 0.0003        | 5.0   | 1135 | 0.0734          | 0.9912   | 0.9911 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  