metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_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: 0.5476190476190477
hushem_5x_deit_base_sgd_001_fold4
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: 1.1129
- Accuracy: 0.5476
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 |
|---|---|---|---|---|
| 1.4194 | 1.0 | 28 | 1.4029 | 0.1667 |
| 1.3727 | 2.0 | 56 | 1.3926 | 0.1667 |
| 1.3518 | 3.0 | 84 | 1.3828 | 0.1905 |
| 1.3497 | 4.0 | 112 | 1.3744 | 0.1905 |
| 1.3305 | 5.0 | 140 | 1.3656 | 0.2381 |
| 1.2982 | 6.0 | 168 | 1.3571 | 0.2619 |
| 1.2935 | 7.0 | 196 | 1.3493 | 0.2619 |
| 1.2822 | 8.0 | 224 | 1.3412 | 0.2857 |
| 1.2479 | 9.0 | 252 | 1.3334 | 0.3095 |
| 1.2377 | 10.0 | 280 | 1.3251 | 0.3333 |
| 1.2239 | 11.0 | 308 | 1.3164 | 0.3095 |
| 1.2188 | 12.0 | 336 | 1.3079 | 0.3095 |
| 1.2085 | 13.0 | 364 | 1.2995 | 0.3095 |
| 1.1996 | 14.0 | 392 | 1.2913 | 0.3333 |
| 1.1629 | 15.0 | 420 | 1.2831 | 0.3810 |
| 1.1847 | 16.0 | 448 | 1.2748 | 0.4048 |
| 1.1633 | 17.0 | 476 | 1.2664 | 0.4048 |
| 1.1189 | 18.0 | 504 | 1.2580 | 0.4048 |
| 1.1351 | 19.0 | 532 | 1.2497 | 0.4286 |
| 1.1255 | 20.0 | 560 | 1.2415 | 0.4286 |
| 1.0873 | 21.0 | 588 | 1.2339 | 0.4524 |
| 1.0919 | 22.0 | 616 | 1.2256 | 0.4524 |
| 1.0941 | 23.0 | 644 | 1.2182 | 0.4524 |
| 1.0702 | 24.0 | 672 | 1.2106 | 0.4762 |
| 1.0623 | 25.0 | 700 | 1.2031 | 0.4762 |
| 1.03 | 26.0 | 728 | 1.1958 | 0.4762 |
| 1.0368 | 27.0 | 756 | 1.1889 | 0.4762 |
| 1.0301 | 28.0 | 784 | 1.1818 | 0.4762 |
| 1.0348 | 29.0 | 812 | 1.1756 | 0.5 |
| 1.0312 | 30.0 | 840 | 1.1689 | 0.5 |
| 1.0387 | 31.0 | 868 | 1.1627 | 0.5238 |
| 1.0057 | 32.0 | 896 | 1.1569 | 0.5 |
| 1.0052 | 33.0 | 924 | 1.1517 | 0.5 |
| 0.9799 | 34.0 | 952 | 1.1467 | 0.5 |
| 1.0233 | 35.0 | 980 | 1.1420 | 0.5 |
| 0.9665 | 36.0 | 1008 | 1.1375 | 0.5 |
| 0.976 | 37.0 | 1036 | 1.1338 | 0.5 |
| 0.9856 | 38.0 | 1064 | 1.1303 | 0.5 |
| 0.9687 | 39.0 | 1092 | 1.1270 | 0.5 |
| 0.9553 | 40.0 | 1120 | 1.1240 | 0.5238 |
| 0.9573 | 41.0 | 1148 | 1.1217 | 0.5476 |
| 0.9651 | 42.0 | 1176 | 1.1193 | 0.5476 |
| 0.9476 | 43.0 | 1204 | 1.1173 | 0.5476 |
| 0.938 | 44.0 | 1232 | 1.1158 | 0.5476 |
| 0.9255 | 45.0 | 1260 | 1.1146 | 0.5476 |
| 0.9569 | 46.0 | 1288 | 1.1137 | 0.5476 |
| 0.9503 | 47.0 | 1316 | 1.1131 | 0.5476 |
| 0.9115 | 48.0 | 1344 | 1.1129 | 0.5476 |
| 0.9482 | 49.0 | 1372 | 1.1129 | 0.5476 |
| 0.9401 | 50.0 | 1400 | 1.1129 | 0.5476 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0