Text Classification
Transformers
TensorBoard
Safetensors
English
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use michaelcw02/roberta-human-or-machine-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelcw02/roberta-human-or-machine-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michaelcw02/roberta-human-or-machine-classification", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michaelcw02/roberta-human-or-machine-classification") model = AutoModelForSequenceClassification.from_pretrained("michaelcw02/roberta-human-or-machine-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# roberta-human-or-machine-classification
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on
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It achieves the following results on the evaluation set:
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- Loss: 0.4389
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# roberta-human-or-machine-classification
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [yaful/MAGE](https://huggingface.co/yaful/MAGE) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4389
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