| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - financial_phrasebank |
| metrics: |
| - f1 |
| - accuracy |
| model-index: |
| - name: phrasebank-sentiment-analysis |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: financial_phrasebank |
| type: financial_phrasebank |
| config: sentences_50agree |
| split: train |
| args: sentences_50agree |
| metrics: |
| - name: F1 |
| type: f1 |
| value: 0.8584242505968677 |
| - name: Accuracy |
| type: accuracy |
| value: 0.8700137551581844 |
|
|
| widget: |
| - text: "In the fourth quarter of 2009 , Orion 's net profit went up by 33.8 % year-on-year to EUR33m ." |
| --- |
| |
| <!-- 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. --> |
|
|
| # phrasebank-sentiment-analysis |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the financial_phrasebank dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4698 |
| - F1: 0.8584 |
| - Accuracy: 0.8700 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
| | 0.6113 | 0.94 | 100 | 0.4105 | 0.8210 | 0.8487 | |
| | 0.2869 | 1.89 | 200 | 0.3898 | 0.8331 | 0.8618 | |
| | 0.1563 | 2.83 | 300 | 0.4733 | 0.8356 | 0.8425 | |
| | 0.073 | 3.77 | 400 | 0.4698 | 0.8584 | 0.8700 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.34.1 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.14.1 |
| |
