| | --- |
| | 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 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # financial-sentiment-analysis |
| |
|
| | This model is a fine-tuned version of [ahmedrachid/FinancialBERT](https://huggingface.co/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 |
| | |
