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
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
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