metadata
library_name: transformers
license: apache-2.0
base_model: Ateeqq/ai-vs-human-image-detector
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: results
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: 0.7560975609756098
results
This model is a fine-tuned version of Ateeqq/ai-vs-human-image-detector on the imagefolder dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.7561
- Loss: 1.1782
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.7523 | 1.0 | 58 | 0.6951 | 1.1249 |
| 0.3123 | 2.0 | 116 | 0.7744 | 0.7260 |
| 0.2716 | 3.0 | 174 | 0.7561 | 1.1782 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1