SwinV2 classification architecture
Captured config identifies Swinv2ForImageClassification with a swinv2 model type and 195206006 parameters.
Open Source Model Profile · haywoodsloan
ai-image-detector-deploy
ai-image-detector-deploy is a 195.2M-parameter SwinV2 image-classification model from haywoodsloan. According to the model card, it was trained with AutoTrain and reports 0.9815 validation accuracy.
- Publisher
- haywoodsloan
- Task
- image-classification
- Model type
- swinv2
- License
- apache-2.0
- Library
- transformers
- Publication status
- Accepted · not indexed
Model overview
ai-image-detector-deploy is published by haywoodsloan as an image-classification model. The captured configuration identifies Swinv2ForImageClassification with a swinv2 model type, and Safetensors metadata reports 195206006 parameters. According to the model card, it was trained using AutoTrain for image classification with published validation metrics.
Recorded capabilities
AutoTrain validation metrics
According to the model card, validation metrics include 0.9815 accuracy, 0.9876 F1, 0.9817 precision, 0.9935 recall, 0.9954 AUC, and 0.0858 loss.
Transformers and Safetensors packaging
Hub metadata lists the transformers library with safetensors, swinv2, and image-classification tags.
Use cases in the source record
- Image-classification inference with the Transformers stack, consistent with the captured pipeline tag and library.
Limitations and unknowns
- No training dataset, hyperparameters, label set, or context beyond AutoTrain validation metrics were extracted from this record.
- No local hardware requirement is provided in the current evidence.
- Provider state is historical snapshot data, not independently refreshed current availability.
Source and provenance
Source: haywoodsloan/ai-image-detector-deploy
Captured: Unknown. Processed: 2026-09-07T19:34:46.661312+00:00.
Model Trained Using AutoTrain Problem type: Image Classification Validation Metrics loss: 0.08581268042325974 f1: 0.9875742669136907 precision: 0.9817413946399085 recall: 0.9934768637532133 auc: 0.9953790023764837 accuracy: 0.981488090989126
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