metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_adamax_00001_fold1
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: 0.4222222222222222
hushem_1x_deit_tiny_adamax_00001_fold1
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1341
- Accuracy: 0.4222
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: 1e-05
- 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 | 1.4260 | 0.2 |
| 1.446 | 2.0 | 12 | 1.3794 | 0.2889 |
| 1.446 | 3.0 | 18 | 1.3570 | 0.3556 |
| 1.184 | 4.0 | 24 | 1.3382 | 0.3111 |
| 1.0671 | 5.0 | 30 | 1.3283 | 0.3111 |
| 1.0671 | 6.0 | 36 | 1.3144 | 0.2889 |
| 0.9249 | 7.0 | 42 | 1.2898 | 0.3333 |
| 0.9249 | 8.0 | 48 | 1.2748 | 0.3556 |
| 0.8443 | 9.0 | 54 | 1.2692 | 0.3333 |
| 0.7477 | 10.0 | 60 | 1.2518 | 0.3778 |
| 0.7477 | 11.0 | 66 | 1.2338 | 0.4 |
| 0.662 | 12.0 | 72 | 1.2193 | 0.3778 |
| 0.662 | 13.0 | 78 | 1.2195 | 0.4 |
| 0.622 | 14.0 | 84 | 1.2039 | 0.3778 |
| 0.5154 | 15.0 | 90 | 1.1949 | 0.4 |
| 0.5154 | 16.0 | 96 | 1.1879 | 0.4 |
| 0.4537 | 17.0 | 102 | 1.1810 | 0.4 |
| 0.4537 | 18.0 | 108 | 1.1670 | 0.4 |
| 0.3859 | 19.0 | 114 | 1.1628 | 0.4 |
| 0.3586 | 20.0 | 120 | 1.1721 | 0.4 |
| 0.3586 | 21.0 | 126 | 1.1698 | 0.4222 |
| 0.3151 | 22.0 | 132 | 1.1603 | 0.4 |
| 0.3151 | 23.0 | 138 | 1.1584 | 0.4222 |
| 0.2881 | 24.0 | 144 | 1.1519 | 0.4222 |
| 0.2498 | 25.0 | 150 | 1.1515 | 0.4222 |
| 0.2498 | 26.0 | 156 | 1.1445 | 0.4222 |
| 0.232 | 27.0 | 162 | 1.1430 | 0.4222 |
| 0.232 | 28.0 | 168 | 1.1452 | 0.4222 |
| 0.2183 | 29.0 | 174 | 1.1406 | 0.4222 |
| 0.1798 | 30.0 | 180 | 1.1348 | 0.4222 |
| 0.1798 | 31.0 | 186 | 1.1304 | 0.4222 |
| 0.1811 | 32.0 | 192 | 1.1281 | 0.4222 |
| 0.1811 | 33.0 | 198 | 1.1317 | 0.4222 |
| 0.1748 | 34.0 | 204 | 1.1302 | 0.4222 |
| 0.1492 | 35.0 | 210 | 1.1303 | 0.4222 |
| 0.1492 | 36.0 | 216 | 1.1319 | 0.4222 |
| 0.1477 | 37.0 | 222 | 1.1328 | 0.4222 |
| 0.1477 | 38.0 | 228 | 1.1366 | 0.4222 |
| 0.1357 | 39.0 | 234 | 1.1362 | 0.4222 |
| 0.1379 | 40.0 | 240 | 1.1351 | 0.4222 |
| 0.1379 | 41.0 | 246 | 1.1344 | 0.4222 |
| 0.1325 | 42.0 | 252 | 1.1341 | 0.4222 |
| 0.1325 | 43.0 | 258 | 1.1341 | 0.4222 |
| 0.1377 | 44.0 | 264 | 1.1341 | 0.4222 |
| 0.1332 | 45.0 | 270 | 1.1341 | 0.4222 |
| 0.1332 | 46.0 | 276 | 1.1341 | 0.4222 |
| 0.1323 | 47.0 | 282 | 1.1341 | 0.4222 |
| 0.1323 | 48.0 | 288 | 1.1341 | 0.4222 |
| 0.1276 | 49.0 | 294 | 1.1341 | 0.4222 |
| 0.1376 | 50.0 | 300 | 1.1341 | 0.4222 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1