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_sgd_lr001_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: 0.3111111111111111
hushem_1x_deit_tiny_sgd_lr001_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: 1.4305
- Accuracy: 0.3111
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 | 1.6118 | 0.1778 |
| 1.6924 | 2.0 | 12 | 1.5735 | 0.2222 |
| 1.6924 | 3.0 | 18 | 1.5416 | 0.2222 |
| 1.5478 | 4.0 | 24 | 1.5201 | 0.2444 |
| 1.5093 | 5.0 | 30 | 1.4995 | 0.2889 |
| 1.5093 | 6.0 | 36 | 1.4836 | 0.2889 |
| 1.4614 | 7.0 | 42 | 1.4737 | 0.2889 |
| 1.4614 | 8.0 | 48 | 1.4656 | 0.2889 |
| 1.3895 | 9.0 | 54 | 1.4578 | 0.2222 |
| 1.4002 | 10.0 | 60 | 1.4519 | 0.2667 |
| 1.4002 | 11.0 | 66 | 1.4464 | 0.2667 |
| 1.3595 | 12.0 | 72 | 1.4429 | 0.2667 |
| 1.3595 | 13.0 | 78 | 1.4392 | 0.2667 |
| 1.3506 | 14.0 | 84 | 1.4366 | 0.2222 |
| 1.2804 | 15.0 | 90 | 1.4347 | 0.2 |
| 1.2804 | 16.0 | 96 | 1.4330 | 0.2 |
| 1.2746 | 17.0 | 102 | 1.4333 | 0.2667 |
| 1.2746 | 18.0 | 108 | 1.4332 | 0.2667 |
| 1.2774 | 19.0 | 114 | 1.4327 | 0.2667 |
| 1.2547 | 20.0 | 120 | 1.4313 | 0.2667 |
| 1.2547 | 21.0 | 126 | 1.4295 | 0.2667 |
| 1.2313 | 22.0 | 132 | 1.4282 | 0.2889 |
| 1.2313 | 23.0 | 138 | 1.4285 | 0.2889 |
| 1.2194 | 24.0 | 144 | 1.4285 | 0.2889 |
| 1.2083 | 25.0 | 150 | 1.4272 | 0.2889 |
| 1.2083 | 26.0 | 156 | 1.4286 | 0.3111 |
| 1.1973 | 27.0 | 162 | 1.4278 | 0.3111 |
| 1.1973 | 28.0 | 168 | 1.4278 | 0.3111 |
| 1.1964 | 29.0 | 174 | 1.4276 | 0.3111 |
| 1.2006 | 30.0 | 180 | 1.4293 | 0.3111 |
| 1.2006 | 31.0 | 186 | 1.4290 | 0.3111 |
| 1.1662 | 32.0 | 192 | 1.4295 | 0.3111 |
| 1.1662 | 33.0 | 198 | 1.4297 | 0.3111 |
| 1.1889 | 34.0 | 204 | 1.4294 | 0.3111 |
| 1.1683 | 35.0 | 210 | 1.4293 | 0.3111 |
| 1.1683 | 36.0 | 216 | 1.4299 | 0.3111 |
| 1.1652 | 37.0 | 222 | 1.4302 | 0.3111 |
| 1.1652 | 38.0 | 228 | 1.4307 | 0.3111 |
| 1.1321 | 39.0 | 234 | 1.4308 | 0.3111 |
| 1.1584 | 40.0 | 240 | 1.4306 | 0.3111 |
| 1.1584 | 41.0 | 246 | 1.4304 | 0.3111 |
| 1.1553 | 42.0 | 252 | 1.4305 | 0.3111 |
| 1.1553 | 43.0 | 258 | 1.4305 | 0.3111 |
| 1.168 | 44.0 | 264 | 1.4305 | 0.3111 |
| 1.1533 | 45.0 | 270 | 1.4305 | 0.3111 |
| 1.1533 | 46.0 | 276 | 1.4305 | 0.3111 |
| 1.1682 | 47.0 | 282 | 1.4305 | 0.3111 |
| 1.1682 | 48.0 | 288 | 1.4305 | 0.3111 |
| 1.1255 | 49.0 | 294 | 1.4305 | 0.3111 |
| 1.1698 | 50.0 | 300 | 1.4305 | 0.3111 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1