ai_art_exp1_efficientnetb3
This model is a fine-tuned version of google/efficientnet-b3 on an unknown dataset. It achieves the following results on the evaluation set:
- Accuracy: {'accuracy': 0.86}
- Loss: 0.5031
- Overall Accuracy: 0.86
- Human Accuracy: 0.688
- Ld Accuracy: 0.996
- Sd Accuracy: 0.896
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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss | Overall Accuracy | Human Accuracy | Ld Accuracy | Sd Accuracy |
|---|---|---|---|---|---|---|---|---|
| 0.5418 | 0.992 | 93 | {'accuracy': 0.868} | 0.5072 | 0.868 | 0.7280 | 0.9923 | 0.8753 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1