metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_adamax_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: 0.6341463414634146
hushem_1x_deit_base_adamax_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: 2.8386
- Accuracy: 0.6341
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.4880 | 0.2683 |
| 1.545 | 2.0 | 12 | 1.4136 | 0.2439 |
| 1.545 | 3.0 | 18 | 1.3443 | 0.3171 |
| 1.396 | 4.0 | 24 | 1.1663 | 0.5122 |
| 1.3173 | 5.0 | 30 | 1.2019 | 0.4878 |
| 1.3173 | 6.0 | 36 | 1.2222 | 0.5122 |
| 1.3167 | 7.0 | 42 | 1.4763 | 0.2439 |
| 1.3167 | 8.0 | 48 | 1.1385 | 0.5610 |
| 1.2585 | 9.0 | 54 | 1.3584 | 0.3659 |
| 1.2419 | 10.0 | 60 | 1.0949 | 0.5122 |
| 1.2419 | 11.0 | 66 | 1.1100 | 0.4634 |
| 1.1714 | 12.0 | 72 | 1.2381 | 0.3902 |
| 1.1714 | 13.0 | 78 | 1.4043 | 0.4146 |
| 1.0593 | 14.0 | 84 | 1.1047 | 0.4878 |
| 1.0451 | 15.0 | 90 | 0.9907 | 0.4878 |
| 1.0451 | 16.0 | 96 | 1.3026 | 0.5122 |
| 0.8805 | 17.0 | 102 | 1.0082 | 0.6098 |
| 0.8805 | 18.0 | 108 | 1.1309 | 0.4634 |
| 0.8077 | 19.0 | 114 | 1.2367 | 0.5610 |
| 0.8096 | 20.0 | 120 | 1.4920 | 0.4878 |
| 0.8096 | 21.0 | 126 | 1.8018 | 0.4878 |
| 0.6582 | 22.0 | 132 | 1.5639 | 0.5854 |
| 0.6582 | 23.0 | 138 | 1.2712 | 0.4878 |
| 0.5106 | 24.0 | 144 | 1.1237 | 0.5854 |
| 0.4184 | 25.0 | 150 | 1.6831 | 0.5610 |
| 0.4184 | 26.0 | 156 | 2.0109 | 0.6098 |
| 0.2718 | 27.0 | 162 | 2.2516 | 0.6341 |
| 0.2718 | 28.0 | 168 | 2.0767 | 0.5610 |
| 0.1639 | 29.0 | 174 | 2.6167 | 0.5854 |
| 0.0535 | 30.0 | 180 | 2.8485 | 0.6341 |
| 0.0535 | 31.0 | 186 | 2.7124 | 0.6585 |
| 0.0454 | 32.0 | 192 | 2.8298 | 0.6585 |
| 0.0454 | 33.0 | 198 | 3.2241 | 0.6341 |
| 0.091 | 34.0 | 204 | 2.4575 | 0.5854 |
| 0.1109 | 35.0 | 210 | 3.7388 | 0.5610 |
| 0.1109 | 36.0 | 216 | 2.3707 | 0.7073 |
| 0.0834 | 37.0 | 222 | 2.5281 | 0.6341 |
| 0.0834 | 38.0 | 228 | 3.1120 | 0.6098 |
| 0.0051 | 39.0 | 234 | 2.7929 | 0.6341 |
| 0.0015 | 40.0 | 240 | 2.7025 | 0.6341 |
| 0.0015 | 41.0 | 246 | 2.8185 | 0.6341 |
| 0.0008 | 42.0 | 252 | 2.8386 | 0.6341 |
| 0.0008 | 43.0 | 258 | 2.8386 | 0.6341 |
| 0.0006 | 44.0 | 264 | 2.8386 | 0.6341 |
| 0.0007 | 45.0 | 270 | 2.8386 | 0.6341 |
| 0.0007 | 46.0 | 276 | 2.8386 | 0.6341 |
| 0.0007 | 47.0 | 282 | 2.8386 | 0.6341 |
| 0.0007 | 48.0 | 288 | 2.8386 | 0.6341 |
| 0.0006 | 49.0 | 294 | 2.8386 | 0.6341 |
| 0.0007 | 50.0 | 300 | 2.8386 | 0.6341 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1