NicolaiSivesind/human-vs-machine
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How to use ayatsuri/academic-ai-detector with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ayatsuri/academic-ai-detector") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ayatsuri/academic-ai-detector")
model = AutoModelForSequenceClassification.from_pretrained("ayatsuri/academic-ai-detector")This model is a fine-tuned version of distilbert/distilbert-base-uncased on NicolaiSivesind/human-vs-machine dataset. It achieves the following best results on the evaluation set:
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The following hyperparameters were used during training:
| Set | Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|
| Train | 0.0910 | 0.9937 | 0.9927 | 0.9947 | 0.9937 |
| Validation | 0.0326 | 0.99 | 0.986 | 0.9940 | 0.9900 |
Please use the following citation:
@misc {ayatsuri24,
author = { Bagas Nuriksan },
title = { Academic AI Detector },
url = { https://huggingface.co/ayatsuri/academic-ai-detector }
year = 2024,
publisher = { Hugging Face }
}
Base model
distilbert/distilbert-base-uncased