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_rms_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: 0.4878048780487805
hushem_1x_deit_base_rms_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: 1.3674
- Accuracy: 0.4878
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 | 5.8345 | 0.2683 |
| 4.8133 | 2.0 | 12 | 1.9738 | 0.2439 |
| 4.8133 | 3.0 | 18 | 1.6557 | 0.2439 |
| 2.3825 | 4.0 | 24 | 1.4419 | 0.2439 |
| 1.6511 | 5.0 | 30 | 1.5141 | 0.2439 |
| 1.6511 | 6.0 | 36 | 1.7332 | 0.2683 |
| 1.5506 | 7.0 | 42 | 1.4915 | 0.2439 |
| 1.5506 | 8.0 | 48 | 1.4901 | 0.2683 |
| 1.4941 | 9.0 | 54 | 1.4008 | 0.2683 |
| 1.5024 | 10.0 | 60 | 1.4017 | 0.2439 |
| 1.5024 | 11.0 | 66 | 1.4108 | 0.2683 |
| 1.6905 | 12.0 | 72 | 1.4762 | 0.2439 |
| 1.6905 | 13.0 | 78 | 1.4772 | 0.2439 |
| 1.4363 | 14.0 | 84 | 1.3917 | 0.3659 |
| 1.4324 | 15.0 | 90 | 1.3778 | 0.2439 |
| 1.4324 | 16.0 | 96 | 1.4917 | 0.2439 |
| 1.4176 | 17.0 | 102 | 1.8605 | 0.2439 |
| 1.4176 | 18.0 | 108 | 1.2587 | 0.4634 |
| 1.4153 | 19.0 | 114 | 1.3519 | 0.3171 |
| 1.363 | 20.0 | 120 | 1.2976 | 0.3902 |
| 1.363 | 21.0 | 126 | 1.7214 | 0.3902 |
| 1.2297 | 22.0 | 132 | 1.5932 | 0.3415 |
| 1.2297 | 23.0 | 138 | 1.0760 | 0.5122 |
| 1.1323 | 24.0 | 144 | 1.1518 | 0.4390 |
| 1.0463 | 25.0 | 150 | 1.1823 | 0.4146 |
| 1.0463 | 26.0 | 156 | 1.0632 | 0.4634 |
| 1.0497 | 27.0 | 162 | 1.1057 | 0.5122 |
| 1.0497 | 28.0 | 168 | 0.9873 | 0.4390 |
| 0.9597 | 29.0 | 174 | 1.0710 | 0.5122 |
| 1.0006 | 30.0 | 180 | 1.1482 | 0.4146 |
| 1.0006 | 31.0 | 186 | 1.1124 | 0.4634 |
| 0.934 | 32.0 | 192 | 1.1437 | 0.4146 |
| 0.934 | 33.0 | 198 | 1.1241 | 0.4390 |
| 0.8599 | 34.0 | 204 | 1.1438 | 0.4390 |
| 0.852 | 35.0 | 210 | 1.1783 | 0.4634 |
| 0.852 | 36.0 | 216 | 1.2807 | 0.4878 |
| 0.8357 | 37.0 | 222 | 1.2879 | 0.4878 |
| 0.8357 | 38.0 | 228 | 1.3101 | 0.4390 |
| 0.7932 | 39.0 | 234 | 1.2773 | 0.4878 |
| 0.7254 | 40.0 | 240 | 1.3480 | 0.4878 |
| 0.7254 | 41.0 | 246 | 1.3839 | 0.4878 |
| 0.7183 | 42.0 | 252 | 1.3674 | 0.4878 |
| 0.7183 | 43.0 | 258 | 1.3674 | 0.4878 |
| 0.6348 | 44.0 | 264 | 1.3674 | 0.4878 |
| 0.6561 | 45.0 | 270 | 1.3674 | 0.4878 |
| 0.6561 | 46.0 | 276 | 1.3674 | 0.4878 |
| 0.6538 | 47.0 | 282 | 1.3674 | 0.4878 |
| 0.6538 | 48.0 | 288 | 1.3674 | 0.4878 |
| 0.6489 | 49.0 | 294 | 1.3674 | 0.4878 |
| 0.6536 | 50.0 | 300 | 1.3674 | 0.4878 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0