<!-- 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. -->
dknews-NB-BERT-AI-classifier/
This model is a fine-tuned version of NbAiLab/nb-bert-large on a custom dataset with Danish News articles either generated by GPT-3 or a Danish journalist from a large Danish news media. The task is then to classify whether the article is written by GPT-3 (label = 0) or human (label = 1)
It achieves the following results on the evaluation set (the best model loaded i.e., after 2 epochs)
- Loss: 0.1804
- Accuracy: 0.9574
- F1: 0.9574
- Precision: 0.9576
- Recall: 0.9574
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
The model is trained on Danish news articles either generated by a fine-tuned GPT-3 or a Danish Journalist from a large Danish News Media TV2.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 2502
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.696 | 1.0 | 39 | 0.4926 | 0.8262 | 0.8211 | 0.8672 | 0.8262 |
| 0.4195 | 2.0 | 78 | 0.1804 | 0.9574 | 0.9574 | 0.9576 | 0.9574 |
| 0.1458 | 3.0 | 117 | 0.2810 | 0.9246 | 0.9241 | 0.9344 | 0.9246 |
| 0.0424 | 4.0 | 156 | 0.5893 | 0.8852 | 0.8838 | 0.9041 | 0.8852 |
| 0.0246 | 5.0 | 195 | 1.4776 | 0.7475 | 0.7301 | 0.8321 | 0.7475 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2
