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_001_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: 0.35555555555555557
hushem_1x_deit_tiny_rms_001_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: 1.2949
- Accuracy: 0.3556
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 | 6.6312 | 0.2667 |
| 4.1013 | 2.0 | 12 | 2.1471 | 0.2444 |
| 4.1013 | 3.0 | 18 | 1.7992 | 0.2444 |
| 1.7936 | 4.0 | 24 | 1.5377 | 0.2667 |
| 1.5908 | 5.0 | 30 | 1.6029 | 0.2444 |
| 1.5908 | 6.0 | 36 | 1.5728 | 0.2444 |
| 1.533 | 7.0 | 42 | 1.6272 | 0.2444 |
| 1.533 | 8.0 | 48 | 1.5192 | 0.2667 |
| 1.4887 | 9.0 | 54 | 1.4382 | 0.2444 |
| 1.4288 | 10.0 | 60 | 1.4387 | 0.2444 |
| 1.4288 | 11.0 | 66 | 1.4770 | 0.2667 |
| 1.422 | 12.0 | 72 | 1.3624 | 0.2444 |
| 1.422 | 13.0 | 78 | 1.4332 | 0.2667 |
| 1.4231 | 14.0 | 84 | 1.4892 | 0.2444 |
| 1.385 | 15.0 | 90 | 1.3102 | 0.4222 |
| 1.385 | 16.0 | 96 | 1.3352 | 0.3333 |
| 1.4799 | 17.0 | 102 | 1.6140 | 0.3111 |
| 1.4799 | 18.0 | 108 | 1.4774 | 0.2444 |
| 1.4126 | 19.0 | 114 | 1.3130 | 0.3333 |
| 1.3511 | 20.0 | 120 | 1.2400 | 0.4222 |
| 1.3511 | 21.0 | 126 | 1.5468 | 0.2667 |
| 1.412 | 22.0 | 132 | 1.4525 | 0.2667 |
| 1.412 | 23.0 | 138 | 1.2484 | 0.3778 |
| 1.3184 | 24.0 | 144 | 1.5741 | 0.2444 |
| 1.3429 | 25.0 | 150 | 1.3487 | 0.4444 |
| 1.3429 | 26.0 | 156 | 1.3203 | 0.3111 |
| 1.2824 | 27.0 | 162 | 1.2257 | 0.4222 |
| 1.2824 | 28.0 | 168 | 1.3520 | 0.2222 |
| 1.2504 | 29.0 | 174 | 1.1717 | 0.4667 |
| 1.235 | 30.0 | 180 | 1.2327 | 0.3778 |
| 1.235 | 31.0 | 186 | 1.3371 | 0.4 |
| 1.2286 | 32.0 | 192 | 1.3224 | 0.2889 |
| 1.2286 | 33.0 | 198 | 1.2295 | 0.3778 |
| 1.168 | 34.0 | 204 | 1.2716 | 0.3111 |
| 1.2345 | 35.0 | 210 | 1.2743 | 0.3111 |
| 1.2345 | 36.0 | 216 | 1.3964 | 0.3778 |
| 1.2057 | 37.0 | 222 | 1.3905 | 0.3556 |
| 1.2057 | 38.0 | 228 | 1.2908 | 0.3778 |
| 1.1197 | 39.0 | 234 | 1.2888 | 0.3556 |
| 1.1518 | 40.0 | 240 | 1.2704 | 0.4 |
| 1.1518 | 41.0 | 246 | 1.3067 | 0.3556 |
| 1.1311 | 42.0 | 252 | 1.2949 | 0.3556 |
| 1.1311 | 43.0 | 258 | 1.2949 | 0.3556 |
| 1.109 | 44.0 | 264 | 1.2949 | 0.3556 |
| 1.1464 | 45.0 | 270 | 1.2949 | 0.3556 |
| 1.1464 | 46.0 | 276 | 1.2949 | 0.3556 |
| 1.0982 | 47.0 | 282 | 1.2949 | 0.3556 |
| 1.0982 | 48.0 | 288 | 1.2949 | 0.3556 |
| 1.1635 | 49.0 | 294 | 1.2949 | 0.3556 |
| 1.1115 | 50.0 | 300 | 1.2949 | 0.3556 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1