metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: nsfw-image-detector
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9315615772103526
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