| | --- |
| | base_model: distilbert/distilroberta-base |
| | datasets: |
| | - financial_phrasebank |
| | license: apache-2.0 |
| | metrics: |
| | - accuracy |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: my_miniroberta_model |
| | results: |
| | - task: |
| | type: text-classification |
| | name: Text Classification |
| | dataset: |
| | name: financial_phrasebank |
| | type: financial_phrasebank |
| | config: sentences_allagree |
| | split: train |
| | args: sentences_allagree |
| | metrics: |
| | - type: accuracy |
| | value: 0.9713024282560706 |
| | name: Accuracy |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # my_miniroberta_model |
| |
|
| | This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the financial_phrasebank dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1663 |
| | - Accuracy: 0.9713 |
| | |
| | ## 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 | 227 | 0.2026 | 0.9338 | |
| | | No log | 2.0 | 454 | 0.1337 | 0.9669 | |
| | | 0.2375 | 3.0 | 681 | 0.1639 | 0.9713 | |
| | | 0.2375 | 4.0 | 908 | 0.1499 | 0.9735 | |
| | | 0.0176 | 5.0 | 1135 | 0.1663 | 0.9713 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.42.4 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
