metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_small_adamax_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: 0.5952380952380952
hushem_1x_deit_small_adamax_001_fold4
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: 3.1234
- Accuracy: 0.5952
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 | 1.5633 | 0.2381 |
| 1.7898 | 2.0 | 12 | 1.3816 | 0.2381 |
| 1.7898 | 3.0 | 18 | 1.3607 | 0.2619 |
| 1.4334 | 4.0 | 24 | 1.3501 | 0.2619 |
| 1.3732 | 5.0 | 30 | 1.3553 | 0.2381 |
| 1.3732 | 6.0 | 36 | 1.1841 | 0.4762 |
| 1.3036 | 7.0 | 42 | 1.0576 | 0.5952 |
| 1.3036 | 8.0 | 48 | 1.0689 | 0.5952 |
| 1.2142 | 9.0 | 54 | 1.2296 | 0.5 |
| 1.056 | 10.0 | 60 | 0.7879 | 0.6429 |
| 1.056 | 11.0 | 66 | 0.7199 | 0.7143 |
| 0.921 | 12.0 | 72 | 0.9775 | 0.6190 |
| 0.921 | 13.0 | 78 | 0.8809 | 0.5952 |
| 0.6456 | 14.0 | 84 | 1.0792 | 0.5476 |
| 0.6348 | 15.0 | 90 | 1.0335 | 0.6190 |
| 0.6348 | 16.0 | 96 | 1.7853 | 0.5714 |
| 0.4743 | 17.0 | 102 | 1.5872 | 0.5714 |
| 0.4743 | 18.0 | 108 | 2.0651 | 0.5 |
| 0.2408 | 19.0 | 114 | 2.8369 | 0.4762 |
| 0.2271 | 20.0 | 120 | 2.1149 | 0.6190 |
| 0.2271 | 21.0 | 126 | 1.5722 | 0.6190 |
| 0.3385 | 22.0 | 132 | 2.8555 | 0.5476 |
| 0.3385 | 23.0 | 138 | 2.2068 | 0.6667 |
| 0.0822 | 24.0 | 144 | 2.2969 | 0.6190 |
| 0.0932 | 25.0 | 150 | 1.8785 | 0.7143 |
| 0.0932 | 26.0 | 156 | 3.2275 | 0.5714 |
| 0.0807 | 27.0 | 162 | 2.8847 | 0.5952 |
| 0.0807 | 28.0 | 168 | 3.1184 | 0.5952 |
| 0.0424 | 29.0 | 174 | 2.4583 | 0.6190 |
| 0.0287 | 30.0 | 180 | 2.8305 | 0.5714 |
| 0.0287 | 31.0 | 186 | 3.5171 | 0.5476 |
| 0.0333 | 32.0 | 192 | 3.2119 | 0.5952 |
| 0.0333 | 33.0 | 198 | 2.9811 | 0.5952 |
| 0.0008 | 34.0 | 204 | 3.0451 | 0.5952 |
| 0.0004 | 35.0 | 210 | 3.0670 | 0.5952 |
| 0.0004 | 36.0 | 216 | 3.0857 | 0.5952 |
| 0.0003 | 37.0 | 222 | 3.1009 | 0.5952 |
| 0.0003 | 38.0 | 228 | 3.1113 | 0.5952 |
| 0.0003 | 39.0 | 234 | 3.1177 | 0.5952 |
| 0.0003 | 40.0 | 240 | 3.1213 | 0.5952 |
| 0.0003 | 41.0 | 246 | 3.1231 | 0.5952 |
| 0.0002 | 42.0 | 252 | 3.1234 | 0.5952 |
| 0.0002 | 43.0 | 258 | 3.1234 | 0.5952 |
| 0.0002 | 44.0 | 264 | 3.1234 | 0.5952 |
| 0.0002 | 45.0 | 270 | 3.1234 | 0.5952 |
| 0.0002 | 46.0 | 276 | 3.1234 | 0.5952 |
| 0.0002 | 47.0 | 282 | 3.1234 | 0.5952 |
| 0.0002 | 48.0 | 288 | 3.1234 | 0.5952 |
| 0.0002 | 49.0 | 294 | 3.1234 | 0.5952 |
| 0.0002 | 50.0 | 300 | 3.1234 | 0.5952 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1