SwinV2 image-classification architecture
The captured configuration identifies Swinv2ForImageClassification with model type swinv2 and Transformers support.
Open Source Model Profile · haywoodsloan
ai-image-detector-dev-deploy
ai-image-detector-dev-deploy is a 195.21M-parameter SwinV2-family image-classification model from haywoodsloan. Its card reports AutoTrain validation scores.
- Publisher
- haywoodsloan
- Task
- image-classification
- Model type
- swinv2
- License
- apache-2.0
- Library
- transformers
- Publication status
- Accepted · not indexed
Model overview
ai-image-detector-dev-deploy is published by haywoodsloan as an image-classification model. The captured configuration identifies Swinv2ForImageClassification with model type swinv2, and Safetensors metadata reports about 195.21M parameters. According to the model card, it was trained with AutoTrain for image classification.
Recorded capabilities
Publisher-reported validation scores
According to the model card, AutoTrain validation reports 0.9815 accuracy with 0.9876 F1 and 0.9954 AUC.
Documented deploy lineage
Hub tags link this checkpoint as a fine-tune of haywoodsloan/ai-image-detector-deploy with autotrain tagging.
Use cases in the source record
- AI-versus-real image-classification workflows consistent with the captured image-classification pipeline tag and AutoTrain problem type.
- Hosted image-classification inference using the snapshot-listed hf-inference route, subject to availability refresh.
Limitations and unknowns
- No independent evaluation results were extracted; the reported scores are publisher AutoTrain validation figures.
- No training-dataset composition or image-size details were extracted from this record.
- Provider state is historical snapshot data and should be refreshed before being presented as current.
Source and provenance
Source: haywoodsloan/ai-image-detector-dev-deploy
Captured: Unknown. Processed: 2026-09-07T19:35:22.643241+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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