metadata

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

roberta-base-autextification

This model is a fine-tuned version of 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