Instructions to use ahmetbekcan/CNNGemma-EfficientNet-Multiple-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmetbekcan/CNNGemma-EfficientNet-Multiple-224 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ahmetbekcan/CNNGemma-EfficientNet-Multiple-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
CNNGemma-EfficientNet-Multiple-224
This model was trained from scratch on an unknown dataset.
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5
Training results
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 3.5.0
- Tokenizers 0.20.3
Inference Providers NEW
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