Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use LukeJacob2023/nsfw-image-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LukeJacob2023/nsfw-image-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="LukeJacob2023/nsfw-image-detector") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("LukeJacob2023/nsfw-image-detector") model = AutoModelForImageClassification.from_pretrained("LukeJacob2023/nsfw-image-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
nsfw-image-detector
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8138
- Accuracy: 0.9316
- Accuracy K: 0.9887
You can access 384 version on:
https://huggingface.co/LukeJacob2023/nsfw-image-detector-384
Model description
Labels: ['drawings', 'hentai', 'neutral', 'porn', 'sexy']
Intended uses & limitations
Training and evaluation data
A custom dataset about 28k images, if you need to improve your domain's accurate, you can contribute the dataset to me.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Accuracy K |
|---|---|---|---|---|---|
| 0.7836 | 1.0 | 720 | 0.3188 | 0.9085 | 0.9891 |
| 0.2441 | 2.0 | 1440 | 0.2382 | 0.9257 | 0.9936 |
| 0.1412 | 3.0 | 2160 | 0.2334 | 0.9335 | 0.9932 |
| 0.0857 | 4.0 | 2880 | 0.2934 | 0.9347 | 0.9934 |
| 0.0569 | 5.0 | 3600 | 0.4500 | 0.9307 | 0.9927 |
| 0.0371 | 6.0 | 4320 | 0.5524 | 0.9357 | 0.9910 |
| 0.0232 | 7.0 | 5040 | 0.6691 | 0.9347 | 0.9913 |
| 0.02 | 8.0 | 5760 | 0.7408 | 0.9335 | 0.9917 |
| 0.0154 | 9.0 | 6480 | 0.8138 | 0.9316 | 0.9887 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
- Downloads last month
- 74,237
Model tree for LukeJacob2023/nsfw-image-detector
Base model
google/vit-base-patch16-224-in21kSpaces using LukeJacob2023/nsfw-image-detector 10
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Evaluation results
- Accuracy on imagefolderself-reported0.932