Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use hkivancoral/hushem_40x_deit_base_n_f2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hkivancoral/hushem_40x_deit_base_n_f2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hkivancoral/hushem_40x_deit_base_n_f2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hkivancoral/hushem_40x_deit_base_n_f2") model = AutoModelForImageClassification.from_pretrained("hkivancoral/hushem_40x_deit_base_n_f2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
hushem_40x_deit_base_n_f2
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.4506
- Accuracy: 0.7556
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.039 | 1.0 | 107 | 0.9415 | 0.7333 |
| 0.0142 | 2.0 | 214 | 1.1180 | 0.7556 |
| 0.0006 | 2.99 | 321 | 1.2484 | 0.8 |
| 0.0002 | 4.0 | 429 | 1.2754 | 0.7556 |
| 0.0001 | 5.0 | 536 | 1.3350 | 0.7556 |
| 0.0 | 6.0 | 643 | 1.3982 | 0.7556 |
| 0.0 | 6.99 | 750 | 1.4243 | 0.7556 |
| 0.0 | 8.0 | 858 | 1.4408 | 0.7556 |
| 0.0 | 9.0 | 965 | 1.4480 | 0.7556 |
| 0.0 | 9.98 | 1070 | 1.4506 | 0.7556 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for hkivancoral/hushem_40x_deit_base_n_f2
Base model
facebook/deit-base-patch16-224Evaluation results
- Accuracy on imagefoldertest set self-reported0.756