metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_tiny_sgd_001_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: 0.5238095238095238
hushem_5x_deit_tiny_sgd_001_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: 1.0007
- Accuracy: 0.5238
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: 0.001
- 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 |
|---|---|---|---|---|
| 1.4776 | 1.0 | 28 | 1.5069 | 0.2857 |
| 1.3802 | 2.0 | 56 | 1.4145 | 0.3571 |
| 1.3245 | 3.0 | 84 | 1.3548 | 0.3571 |
| 1.3009 | 4.0 | 112 | 1.3137 | 0.4286 |
| 1.2628 | 5.0 | 140 | 1.2827 | 0.4524 |
| 1.2443 | 6.0 | 168 | 1.2514 | 0.5238 |
| 1.1651 | 7.0 | 196 | 1.2261 | 0.5238 |
| 1.1485 | 8.0 | 224 | 1.2037 | 0.5238 |
| 1.1029 | 9.0 | 252 | 1.1805 | 0.5238 |
| 1.0945 | 10.0 | 280 | 1.1607 | 0.5238 |
| 1.1057 | 11.0 | 308 | 1.1451 | 0.5476 |
| 1.0601 | 12.0 | 336 | 1.1295 | 0.5476 |
| 1.0375 | 13.0 | 364 | 1.1248 | 0.5476 |
| 1.024 | 14.0 | 392 | 1.1065 | 0.5952 |
| 0.9777 | 15.0 | 420 | 1.0997 | 0.5952 |
| 0.9798 | 16.0 | 448 | 1.0984 | 0.5952 |
| 0.9759 | 17.0 | 476 | 1.0858 | 0.5952 |
| 0.9492 | 18.0 | 504 | 1.0744 | 0.5476 |
| 0.911 | 19.0 | 532 | 1.0716 | 0.5952 |
| 0.9409 | 20.0 | 560 | 1.0622 | 0.5476 |
| 0.8706 | 21.0 | 588 | 1.0578 | 0.5476 |
| 0.9232 | 22.0 | 616 | 1.0547 | 0.5952 |
| 0.8639 | 23.0 | 644 | 1.0468 | 0.5 |
| 0.9013 | 24.0 | 672 | 1.0442 | 0.5238 |
| 0.8242 | 25.0 | 700 | 1.0432 | 0.5238 |
| 0.8379 | 26.0 | 728 | 1.0386 | 0.5238 |
| 0.8656 | 27.0 | 756 | 1.0271 | 0.5238 |
| 0.8539 | 28.0 | 784 | 1.0232 | 0.5 |
| 0.831 | 29.0 | 812 | 1.0228 | 0.5238 |
| 0.7984 | 30.0 | 840 | 1.0256 | 0.5 |
| 0.8188 | 31.0 | 868 | 1.0204 | 0.5 |
| 0.8337 | 32.0 | 896 | 1.0202 | 0.5 |
| 0.7879 | 33.0 | 924 | 1.0178 | 0.5 |
| 0.7864 | 34.0 | 952 | 1.0219 | 0.5238 |
| 0.8414 | 35.0 | 980 | 1.0150 | 0.5238 |
| 0.8067 | 36.0 | 1008 | 1.0140 | 0.5238 |
| 0.7647 | 37.0 | 1036 | 1.0119 | 0.5238 |
| 0.7807 | 38.0 | 1064 | 1.0087 | 0.5238 |
| 0.7751 | 39.0 | 1092 | 1.0072 | 0.5238 |
| 0.7728 | 40.0 | 1120 | 1.0064 | 0.5238 |
| 0.7814 | 41.0 | 1148 | 1.0052 | 0.5238 |
| 0.7361 | 42.0 | 1176 | 1.0026 | 0.5238 |
| 0.7838 | 43.0 | 1204 | 1.0019 | 0.5238 |
| 0.7388 | 44.0 | 1232 | 1.0012 | 0.5238 |
| 0.7605 | 45.0 | 1260 | 1.0006 | 0.5238 |
| 0.7578 | 46.0 | 1288 | 1.0005 | 0.5238 |
| 0.7479 | 47.0 | 1316 | 1.0010 | 0.5238 |
| 0.7186 | 48.0 | 1344 | 1.0007 | 0.5238 |
| 0.7471 | 49.0 | 1372 | 1.0007 | 0.5238 |
| 0.7354 | 50.0 | 1400 | 1.0007 | 0.5238 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0