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_lr0001_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: 0.16666666666666666
hushem_1x_deit_tiny_sgd_lr0001_fold4
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: 1.4980
- Accuracy: 0.1667
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: 0.0001
- 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 | 1.5601 | 0.1905 |
| 1.6045 | 2.0 | 12 | 1.5566 | 0.1905 |
| 1.6045 | 3.0 | 18 | 1.5532 | 0.1905 |
| 1.6142 | 4.0 | 24 | 1.5500 | 0.1905 |
| 1.6266 | 5.0 | 30 | 1.5471 | 0.1905 |
| 1.6266 | 6.0 | 36 | 1.5442 | 0.1905 |
| 1.6101 | 7.0 | 42 | 1.5414 | 0.1905 |
| 1.6101 | 8.0 | 48 | 1.5385 | 0.1905 |
| 1.6089 | 9.0 | 54 | 1.5358 | 0.1905 |
| 1.5908 | 10.0 | 60 | 1.5333 | 0.1905 |
| 1.5908 | 11.0 | 66 | 1.5308 | 0.1905 |
| 1.5657 | 12.0 | 72 | 1.5284 | 0.1905 |
| 1.5657 | 13.0 | 78 | 1.5261 | 0.1905 |
| 1.6049 | 14.0 | 84 | 1.5240 | 0.1905 |
| 1.5586 | 15.0 | 90 | 1.5222 | 0.1905 |
| 1.5586 | 16.0 | 96 | 1.5201 | 0.1905 |
| 1.5639 | 17.0 | 102 | 1.5182 | 0.1905 |
| 1.5639 | 18.0 | 108 | 1.5166 | 0.1905 |
| 1.5536 | 19.0 | 114 | 1.5151 | 0.1905 |
| 1.5821 | 20.0 | 120 | 1.5136 | 0.1905 |
| 1.5821 | 21.0 | 126 | 1.5122 | 0.1905 |
| 1.5341 | 22.0 | 132 | 1.5109 | 0.1905 |
| 1.5341 | 23.0 | 138 | 1.5096 | 0.1905 |
| 1.6078 | 24.0 | 144 | 1.5084 | 0.1905 |
| 1.5121 | 25.0 | 150 | 1.5073 | 0.1905 |
| 1.5121 | 26.0 | 156 | 1.5061 | 0.1905 |
| 1.5521 | 27.0 | 162 | 1.5050 | 0.1905 |
| 1.5521 | 28.0 | 168 | 1.5041 | 0.1905 |
| 1.5505 | 29.0 | 174 | 1.5033 | 0.1905 |
| 1.5712 | 30.0 | 180 | 1.5025 | 0.1905 |
| 1.5712 | 31.0 | 186 | 1.5017 | 0.1905 |
| 1.5865 | 32.0 | 192 | 1.5010 | 0.1905 |
| 1.5865 | 33.0 | 198 | 1.5005 | 0.1905 |
| 1.4766 | 34.0 | 204 | 1.4999 | 0.1905 |
| 1.5501 | 35.0 | 210 | 1.4994 | 0.1905 |
| 1.5501 | 36.0 | 216 | 1.4990 | 0.1905 |
| 1.5465 | 37.0 | 222 | 1.4987 | 0.1667 |
| 1.5465 | 38.0 | 228 | 1.4984 | 0.1667 |
| 1.5254 | 39.0 | 234 | 1.4982 | 0.1667 |
| 1.575 | 40.0 | 240 | 1.4980 | 0.1667 |
| 1.575 | 41.0 | 246 | 1.4980 | 0.1667 |
| 1.5455 | 42.0 | 252 | 1.4980 | 0.1667 |
| 1.5455 | 43.0 | 258 | 1.4980 | 0.1667 |
| 1.5648 | 44.0 | 264 | 1.4980 | 0.1667 |
| 1.5279 | 45.0 | 270 | 1.4980 | 0.1667 |
| 1.5279 | 46.0 | 276 | 1.4980 | 0.1667 |
| 1.5492 | 47.0 | 282 | 1.4980 | 0.1667 |
| 1.5492 | 48.0 | 288 | 1.4980 | 0.1667 |
| 1.5479 | 49.0 | 294 | 1.4980 | 0.1667 |
| 1.5321 | 50.0 | 300 | 1.4980 | 0.1667 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1