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_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_base_sgd_001_fold5
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: 1.0680
- 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 |
|---|---|---|---|---|
| 1.4163 | 1.0 | 28 | 1.3604 | 0.1951 |
| 1.3947 | 2.0 | 56 | 1.3473 | 0.2195 |
| 1.3604 | 3.0 | 84 | 1.3349 | 0.2683 |
| 1.3392 | 4.0 | 112 | 1.3241 | 0.2927 |
| 1.3444 | 5.0 | 140 | 1.3143 | 0.3171 |
| 1.3238 | 6.0 | 168 | 1.3050 | 0.3415 |
| 1.3103 | 7.0 | 196 | 1.2955 | 0.3659 |
| 1.2905 | 8.0 | 224 | 1.2862 | 0.3902 |
| 1.2713 | 9.0 | 252 | 1.2769 | 0.4146 |
| 1.2521 | 10.0 | 280 | 1.2674 | 0.4390 |
| 1.2419 | 11.0 | 308 | 1.2580 | 0.4390 |
| 1.2274 | 12.0 | 336 | 1.2492 | 0.4634 |
| 1.2017 | 13.0 | 364 | 1.2403 | 0.5122 |
| 1.2089 | 14.0 | 392 | 1.2314 | 0.5366 |
| 1.1882 | 15.0 | 420 | 1.2229 | 0.5366 |
| 1.1838 | 16.0 | 448 | 1.2144 | 0.5610 |
| 1.1566 | 17.0 | 476 | 1.2059 | 0.5610 |
| 1.1584 | 18.0 | 504 | 1.1980 | 0.6098 |
| 1.1748 | 19.0 | 532 | 1.1896 | 0.6098 |
| 1.1362 | 20.0 | 560 | 1.1817 | 0.6098 |
| 1.1338 | 21.0 | 588 | 1.1741 | 0.5854 |
| 1.1033 | 22.0 | 616 | 1.1667 | 0.5854 |
| 1.0957 | 23.0 | 644 | 1.1590 | 0.5854 |
| 1.0836 | 24.0 | 672 | 1.1521 | 0.5854 |
| 1.0697 | 25.0 | 700 | 1.1452 | 0.5610 |
| 1.078 | 26.0 | 728 | 1.1389 | 0.5366 |
| 1.0636 | 27.0 | 756 | 1.1332 | 0.5610 |
| 1.0604 | 28.0 | 784 | 1.1274 | 0.5366 |
| 1.0075 | 29.0 | 812 | 1.1217 | 0.5610 |
| 1.0554 | 30.0 | 840 | 1.1163 | 0.5610 |
| 1.0238 | 31.0 | 868 | 1.1110 | 0.5610 |
| 0.9869 | 32.0 | 896 | 1.1060 | 0.5854 |
| 0.9963 | 33.0 | 924 | 1.1019 | 0.5610 |
| 1.0156 | 34.0 | 952 | 1.0973 | 0.5854 |
| 0.9827 | 35.0 | 980 | 1.0931 | 0.5854 |
| 0.9853 | 36.0 | 1008 | 1.0896 | 0.5854 |
| 0.9677 | 37.0 | 1036 | 1.0862 | 0.5854 |
| 0.9703 | 38.0 | 1064 | 1.0831 | 0.5854 |
| 0.9924 | 39.0 | 1092 | 1.0803 | 0.5854 |
| 0.9509 | 40.0 | 1120 | 1.0778 | 0.5854 |
| 0.9744 | 41.0 | 1148 | 1.0755 | 0.5854 |
| 0.957 | 42.0 | 1176 | 1.0735 | 0.5854 |
| 0.958 | 43.0 | 1204 | 1.0718 | 0.5854 |
| 0.965 | 44.0 | 1232 | 1.0705 | 0.5854 |
| 0.9524 | 45.0 | 1260 | 1.0695 | 0.5854 |
| 0.9551 | 46.0 | 1288 | 1.0687 | 0.5854 |
| 0.9588 | 47.0 | 1316 | 1.0682 | 0.5854 |
| 0.9894 | 48.0 | 1344 | 1.0680 | 0.5854 |
| 0.9401 | 49.0 | 1372 | 1.0680 | 0.5854 |
| 0.9662 | 50.0 | 1400 | 1.0680 | 0.5854 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0