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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- au_tex_tification |
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metrics: |
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- accuracy |
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model-index: |
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- name: roberta-base-autextification |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: au_tex_tification |
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type: au_tex_tification |
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config: detection_en |
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split: train |
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args: detection_en |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6296720410406742 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta-base-autextification |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the au_tex_tification dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3253 |
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- Accuracy: 0.6297 |
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- Roc Auc: 0.8980 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:| |
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| 0.4844 | 1.0 | 3385 | 0.2904 | 0.9057 | 0.9745 | |
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| 0.1311 | 2.0 | 6770 | 0.4360 | 0.8997 | 0.9817 | |
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| 0.1576 | 3.0 | 10155 | 0.5514 | 0.9088 | 0.9837 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.14.1 |
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