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