readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - financial
  - stocks
  - sentiment
  widget:
  - text: "Operating profit totaled EUR 9.4 mn , down from EUR 11.7 mn in 2004 ."
  datasets:
  - financial_phrasebank
  metrics:
  - accuracy
  model-index:
  - name: distilRoberta-financial-sentiment
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: financial_phrasebank
        type: financial_phrasebank
        args: sentences_allagree
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9823008849557522
  ---
  
  <!-- 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. -->
  
  # distilRoberta-financial-sentiment
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the financial_phrasebank dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1116
  - Accuracy: 0.9823
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 255  | 0.1670          | 0.9646   |
  | 0.209         | 2.0   | 510  | 0.2290          | 0.9558   |
  | 0.209         | 3.0   | 765  | 0.2044          | 0.9558   |
  | 0.0326        | 4.0   | 1020 | 0.1116          | 0.9823   |
  | 0.0326        | 5.0   | 1275 | 0.1127          | 0.9779   |
  
  
  ### Framework versions
  
  - Transformers 4.10.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  