README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - financial_phrasebank
metrics:
  - accuracy
  - f1
base_model: ahmedrachid/FinancialBERT
model-index:
  - name: financial-sentiment-analysis
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: financial_phrasebank
          type: financial_phrasebank
          args: sentences_allagree
        metrics:
          - type: accuracy
            value: 0.9924242424242424
            name: Accuracy
          - type: f1
            value: 0.9924242424242424
            name: F1

financial-sentiment-analysis

This model is a fine-tuned version of ahmedrachid/FinancialBERT on the financial_phrasebank dataset. It achieves the following results on the evaluation set:

• Loss: 0.0395
• Accuracy: 0.9924
• F1: 0.9924

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Framework versions

• Transformers 4.19.1
• Pytorch 1.11.0+cu113
• Datasets 2.2.1
• Tokenizers 0.12.1