metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_sgd_001_fold5
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: 0.5853658536585366
hushem_5x_deit_small_sgd_001_fold5
This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0219
- Accuracy: 0.5854
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 |
|---|---|---|---|---|
| 1.5389 | 1.0 | 28 | 1.4343 | 0.2439 |
| 1.3921 | 2.0 | 56 | 1.3847 | 0.2683 |
| 1.3749 | 3.0 | 84 | 1.3585 | 0.3659 |
| 1.3126 | 4.0 | 112 | 1.3409 | 0.3659 |
| 1.3117 | 5.0 | 140 | 1.3251 | 0.3659 |
| 1.3121 | 6.0 | 168 | 1.3119 | 0.3415 |
| 1.2628 | 7.0 | 196 | 1.2980 | 0.3415 |
| 1.2308 | 8.0 | 224 | 1.2843 | 0.3659 |
| 1.2428 | 9.0 | 252 | 1.2711 | 0.4146 |
| 1.1961 | 10.0 | 280 | 1.2591 | 0.4146 |
| 1.1795 | 11.0 | 308 | 1.2486 | 0.3902 |
| 1.1594 | 12.0 | 336 | 1.2381 | 0.3902 |
| 1.1371 | 13.0 | 364 | 1.2260 | 0.3902 |
| 1.1217 | 14.0 | 392 | 1.2140 | 0.4390 |
| 1.0975 | 15.0 | 420 | 1.2018 | 0.4634 |
| 1.1139 | 16.0 | 448 | 1.1910 | 0.4878 |
| 1.0797 | 17.0 | 476 | 1.1802 | 0.4878 |
| 1.0813 | 18.0 | 504 | 1.1682 | 0.4878 |
| 1.0619 | 19.0 | 532 | 1.1572 | 0.4878 |
| 1.0398 | 20.0 | 560 | 1.1467 | 0.5122 |
| 1.0215 | 21.0 | 588 | 1.1362 | 0.5122 |
| 1.0014 | 22.0 | 616 | 1.1280 | 0.5366 |
| 1.0047 | 23.0 | 644 | 1.1216 | 0.5610 |
| 0.9823 | 24.0 | 672 | 1.1144 | 0.5610 |
| 0.9814 | 25.0 | 700 | 1.1058 | 0.5610 |
| 0.9822 | 26.0 | 728 | 1.0976 | 0.5610 |
| 0.9448 | 27.0 | 756 | 1.0916 | 0.5366 |
| 0.9805 | 28.0 | 784 | 1.0839 | 0.5366 |
| 0.9187 | 29.0 | 812 | 1.0780 | 0.5366 |
| 0.9659 | 30.0 | 840 | 1.0725 | 0.5366 |
| 0.9135 | 31.0 | 868 | 1.0663 | 0.5610 |
| 0.889 | 32.0 | 896 | 1.0628 | 0.5610 |
| 0.9089 | 33.0 | 924 | 1.0587 | 0.5610 |
| 0.9062 | 34.0 | 952 | 1.0524 | 0.5610 |
| 0.9029 | 35.0 | 980 | 1.0479 | 0.5610 |
| 0.8924 | 36.0 | 1008 | 1.0439 | 0.5854 |
| 0.8694 | 37.0 | 1036 | 1.0402 | 0.5854 |
| 0.8578 | 38.0 | 1064 | 1.0365 | 0.5610 |
| 0.8992 | 39.0 | 1092 | 1.0340 | 0.5854 |
| 0.8586 | 40.0 | 1120 | 1.0317 | 0.5854 |
| 0.8737 | 41.0 | 1148 | 1.0296 | 0.5854 |
| 0.8517 | 42.0 | 1176 | 1.0278 | 0.5854 |
| 0.8537 | 43.0 | 1204 | 1.0257 | 0.5854 |
| 0.8642 | 44.0 | 1232 | 1.0243 | 0.5854 |
| 0.871 | 45.0 | 1260 | 1.0234 | 0.5854 |
| 0.8594 | 46.0 | 1288 | 1.0226 | 0.5854 |
| 0.8675 | 47.0 | 1316 | 1.0221 | 0.5854 |
| 0.874 | 48.0 | 1344 | 1.0219 | 0.5854 |
| 0.8459 | 49.0 | 1372 | 1.0219 | 0.5854 |
| 0.8538 | 50.0 | 1400 | 1.0219 | 0.5854 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0