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_rms_lr0001_fold2
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: 0.6888888888888889
hushem_1x_deit_tiny_rms_lr0001_fold2
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: 1.7300
- Accuracy: 0.6889
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 | 3.0363 | 0.2444 |
| 2.6477 | 2.0 | 12 | 1.6954 | 0.2444 |
| 2.6477 | 3.0 | 18 | 1.4980 | 0.2444 |
| 1.482 | 4.0 | 24 | 1.3454 | 0.3556 |
| 1.4166 | 5.0 | 30 | 1.3094 | 0.4 |
| 1.4166 | 6.0 | 36 | 1.6095 | 0.2444 |
| 1.3414 | 7.0 | 42 | 1.9023 | 0.2444 |
| 1.3414 | 8.0 | 48 | 1.3957 | 0.2222 |
| 1.2396 | 9.0 | 54 | 1.1738 | 0.4 |
| 1.2068 | 10.0 | 60 | 1.2312 | 0.4889 |
| 1.2068 | 11.0 | 66 | 1.0903 | 0.6 |
| 0.9263 | 12.0 | 72 | 0.9211 | 0.5778 |
| 0.9263 | 13.0 | 78 | 1.1912 | 0.4444 |
| 0.8539 | 14.0 | 84 | 1.2631 | 0.5333 |
| 0.6672 | 15.0 | 90 | 1.2596 | 0.5111 |
| 0.6672 | 16.0 | 96 | 1.3999 | 0.4889 |
| 0.5299 | 17.0 | 102 | 1.2988 | 0.5556 |
| 0.5299 | 18.0 | 108 | 1.3328 | 0.5333 |
| 0.3853 | 19.0 | 114 | 1.0485 | 0.6222 |
| 0.332 | 20.0 | 120 | 1.1428 | 0.5778 |
| 0.332 | 21.0 | 126 | 1.0486 | 0.6444 |
| 0.1829 | 22.0 | 132 | 1.0866 | 0.6667 |
| 0.1829 | 23.0 | 138 | 1.7727 | 0.5778 |
| 0.111 | 24.0 | 144 | 1.2950 | 0.6889 |
| 0.0444 | 25.0 | 150 | 1.4579 | 0.7111 |
| 0.0444 | 26.0 | 156 | 1.4269 | 0.6889 |
| 0.0017 | 27.0 | 162 | 1.4804 | 0.6889 |
| 0.0017 | 28.0 | 168 | 1.5281 | 0.6889 |
| 0.0007 | 29.0 | 174 | 1.5658 | 0.6667 |
| 0.0005 | 30.0 | 180 | 1.5943 | 0.6667 |
| 0.0005 | 31.0 | 186 | 1.6212 | 0.6667 |
| 0.0004 | 32.0 | 192 | 1.6444 | 0.6667 |
| 0.0004 | 33.0 | 198 | 1.6608 | 0.6667 |
| 0.0003 | 34.0 | 204 | 1.6759 | 0.6667 |
| 0.0003 | 35.0 | 210 | 1.6896 | 0.6667 |
| 0.0003 | 36.0 | 216 | 1.7018 | 0.6667 |
| 0.0003 | 37.0 | 222 | 1.7108 | 0.6889 |
| 0.0003 | 38.0 | 228 | 1.7185 | 0.6889 |
| 0.0003 | 39.0 | 234 | 1.7237 | 0.6889 |
| 0.0002 | 40.0 | 240 | 1.7275 | 0.6889 |
| 0.0002 | 41.0 | 246 | 1.7295 | 0.6889 |
| 0.0003 | 42.0 | 252 | 1.7300 | 0.6889 |
| 0.0003 | 43.0 | 258 | 1.7300 | 0.6889 |
| 0.0002 | 44.0 | 264 | 1.7300 | 0.6889 |
| 0.0002 | 45.0 | 270 | 1.7300 | 0.6889 |
| 0.0002 | 46.0 | 276 | 1.7300 | 0.6889 |
| 0.0002 | 47.0 | 282 | 1.7300 | 0.6889 |
| 0.0002 | 48.0 | 288 | 1.7300 | 0.6889 |
| 0.0002 | 49.0 | 294 | 1.7300 | 0.6889 |
| 0.0002 | 50.0 | 300 | 1.7300 | 0.6889 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1