metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_00001_fold4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.2857142857142857
hushem_1x_deit_tiny_sgd_00001_fold4
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.6751
- Accuracy: 0.2857
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: 1e-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_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.6974 | 0.2857 |
| 1.71 | 2.0 | 12 | 1.6962 | 0.2857 |
| 1.71 | 3.0 | 18 | 1.6951 | 0.2857 |
| 1.7036 | 4.0 | 24 | 1.6940 | 0.2857 |
| 1.7465 | 5.0 | 30 | 1.6930 | 0.2857 |
| 1.7465 | 6.0 | 36 | 1.6921 | 0.2857 |
| 1.709 | 7.0 | 42 | 1.6911 | 0.2857 |
| 1.709 | 8.0 | 48 | 1.6901 | 0.2857 |
| 1.712 | 9.0 | 54 | 1.6892 | 0.2857 |
| 1.7048 | 10.0 | 60 | 1.6882 | 0.2857 |
| 1.7048 | 11.0 | 66 | 1.6874 | 0.2857 |
| 1.6828 | 12.0 | 72 | 1.6866 | 0.2857 |
| 1.6828 | 13.0 | 78 | 1.6858 | 0.2857 |
| 1.7139 | 14.0 | 84 | 1.6850 | 0.2857 |
| 1.719 | 15.0 | 90 | 1.6842 | 0.2857 |
| 1.719 | 16.0 | 96 | 1.6835 | 0.2857 |
| 1.6904 | 17.0 | 102 | 1.6828 | 0.2857 |
| 1.6904 | 18.0 | 108 | 1.6821 | 0.2857 |
| 1.7154 | 19.0 | 114 | 1.6815 | 0.2857 |
| 1.7326 | 20.0 | 120 | 1.6809 | 0.2857 |
| 1.7326 | 21.0 | 126 | 1.6804 | 0.2857 |
| 1.6942 | 22.0 | 132 | 1.6799 | 0.2857 |
| 1.6942 | 23.0 | 138 | 1.6794 | 0.2857 |
| 1.6945 | 24.0 | 144 | 1.6789 | 0.2857 |
| 1.728 | 25.0 | 150 | 1.6784 | 0.2857 |
| 1.728 | 26.0 | 156 | 1.6780 | 0.2857 |
| 1.7026 | 27.0 | 162 | 1.6776 | 0.2857 |
| 1.7026 | 28.0 | 168 | 1.6772 | 0.2857 |
| 1.7403 | 29.0 | 174 | 1.6769 | 0.2857 |
| 1.6716 | 30.0 | 180 | 1.6766 | 0.2857 |
| 1.6716 | 31.0 | 186 | 1.6764 | 0.2857 |
| 1.6806 | 32.0 | 192 | 1.6761 | 0.2857 |
| 1.6806 | 33.0 | 198 | 1.6759 | 0.2857 |
| 1.6988 | 34.0 | 204 | 1.6757 | 0.2857 |
| 1.6893 | 35.0 | 210 | 1.6755 | 0.2857 |
| 1.6893 | 36.0 | 216 | 1.6754 | 0.2857 |
| 1.6718 | 37.0 | 222 | 1.6753 | 0.2857 |
| 1.6718 | 38.0 | 228 | 1.6752 | 0.2857 |
| 1.7279 | 39.0 | 234 | 1.6751 | 0.2857 |
| 1.6803 | 40.0 | 240 | 1.6751 | 0.2857 |
| 1.6803 | 41.0 | 246 | 1.6751 | 0.2857 |
| 1.6785 | 42.0 | 252 | 1.6751 | 0.2857 |
| 1.6785 | 43.0 | 258 | 1.6751 | 0.2857 |
| 1.7169 | 44.0 | 264 | 1.6751 | 0.2857 |
| 1.6924 | 45.0 | 270 | 1.6751 | 0.2857 |
| 1.6924 | 46.0 | 276 | 1.6751 | 0.2857 |
| 1.6961 | 47.0 | 282 | 1.6751 | 0.2857 |
| 1.6961 | 48.0 | 288 | 1.6751 | 0.2857 |
| 1.7415 | 49.0 | 294 | 1.6751 | 0.2857 |
| 1.681 | 50.0 | 300 | 1.6751 | 0.2857 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0