almanach / xlmr-chatgptdetect-noisy

huggingface.co
Total runs: 56
24-hour runs: -22
7-day runs: -11
30-day runs: 46
Model's Last Updated: March 22 2024
text-classification

Introduction of xlmr-chatgptdetect-noisy

Model Details of xlmr-chatgptdetect-noisy

xlmr-chatgptdetect-noisy

Multilingual ChatGPT detection model from Towards a Robust Detection of Language Model-Generated Text: Is ChatGPT that easy to detect?

This model is a fine-tuned version of xlm-roberta-base on the HC3 FULL_MULTI_1.0_0.5_0.5 dataset with noise added. It achieves the following results on the:

Evaluation set:

  • Loss: 0.1573
  • F1: 0.9633

Test Set:

  • F1: 0.97

Adversarial:

  • F1: 0.45
Model description

This a model trained to detect text created by ChatGPT in French. The training data is the combination of the hc3_fr_full and hc3_en_full subsets of almanach/hc3_multi , but with added misspelling and homoglyph attacks.

Intended uses & limitations

This model is for research purposes only. It is not intended to be used in production as we said in our paper:

We would like to emphasize that our study does not claim to have produced an universally accurate detector. Our strong results are based on in-domain testing and, unsurprisingly, do not generalize in out-of-domain scenarios. This is even more so when used on text specifically designed to fool language model detectors and on text intentionally stylistically similar to ChatGPT-generated text, especially instructional text.

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5.0
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss F1
0.0317 1.0 8538 0.1732 0.9492
0.008 2.0 17076 0.3541 0.9270
0.0085 3.0 25614 0.1161 0.9726
0.0015 4.0 34152 0.2557 0.9516
0.0 5.0 42690 0.2286 0.9650
Framework versions
  • Transformers 4.26.1
  • Pytorch 1.11.0+cu115
  • Datasets 2.8.0
  • Tokenizers 0.13.2

Runs of almanach xlmr-chatgptdetect-noisy on huggingface.co

56
Total runs
-22
24-hour runs
-21
3-day runs
-11
7-day runs
46
30-day runs

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