| | --- |
| | license: mit |
| | base_model: roberta-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - au_tex_tification |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: roberta-base-autextification |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: au_tex_tification |
| | type: au_tex_tification |
| | config: detection_en |
| | split: train |
| | args: detection_en |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6296720410406742 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # roberta-base-autextification |
| |
|
| | This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the au_tex_tification dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.3253 |
| | - Accuracy: 0.6297 |
| | - Roc Auc: 0.8980 |
| |
|
| | ## 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: 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: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:| |
| | | 0.4844 | 1.0 | 3385 | 0.2904 | 0.9057 | 0.9745 | |
| | | 0.1311 | 2.0 | 6770 | 0.4360 | 0.8997 | 0.9817 | |
| | | 0.1576 | 3.0 | 10155 | 0.5514 | 0.9088 | 0.9837 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.14.1 |
| |
|
