metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_rms_001_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: 0.5714285714285714
hushem_1x_deit_base_rms_001_fold4
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.2820
- Accuracy: 0.5714
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 | 6.4622 | 0.2381 |
| 4.4464 | 2.0 | 12 | 3.3632 | 0.2381 |
| 4.4464 | 3.0 | 18 | 1.7517 | 0.2619 |
| 2.081 | 4.0 | 24 | 1.7192 | 0.2381 |
| 1.6572 | 5.0 | 30 | 1.4331 | 0.2619 |
| 1.6572 | 6.0 | 36 | 1.7438 | 0.2381 |
| 1.515 | 7.0 | 42 | 1.5334 | 0.2381 |
| 1.515 | 8.0 | 48 | 1.4427 | 0.2619 |
| 1.4729 | 9.0 | 54 | 1.4737 | 0.2619 |
| 1.4733 | 10.0 | 60 | 1.3911 | 0.2381 |
| 1.4733 | 11.0 | 66 | 1.4837 | 0.2619 |
| 1.4345 | 12.0 | 72 | 1.3420 | 0.3333 |
| 1.4345 | 13.0 | 78 | 1.3532 | 0.3095 |
| 1.37 | 14.0 | 84 | 1.2042 | 0.5714 |
| 1.3487 | 15.0 | 90 | 1.2734 | 0.3095 |
| 1.3487 | 16.0 | 96 | 1.1311 | 0.4286 |
| 1.2658 | 17.0 | 102 | 1.1548 | 0.4762 |
| 1.2658 | 18.0 | 108 | 1.2031 | 0.3571 |
| 1.2896 | 19.0 | 114 | 1.2313 | 0.4762 |
| 1.2598 | 20.0 | 120 | 1.3330 | 0.3810 |
| 1.2598 | 21.0 | 126 | 1.1274 | 0.5238 |
| 1.2329 | 22.0 | 132 | 1.2033 | 0.5238 |
| 1.2329 | 23.0 | 138 | 1.1130 | 0.5 |
| 1.2013 | 24.0 | 144 | 1.1588 | 0.5 |
| 1.1821 | 25.0 | 150 | 1.3546 | 0.3810 |
| 1.1821 | 26.0 | 156 | 1.1188 | 0.4524 |
| 1.1779 | 27.0 | 162 | 1.1678 | 0.3571 |
| 1.1779 | 28.0 | 168 | 1.2401 | 0.3333 |
| 1.1114 | 29.0 | 174 | 1.0781 | 0.5476 |
| 1.1371 | 30.0 | 180 | 1.0969 | 0.5476 |
| 1.1371 | 31.0 | 186 | 1.2482 | 0.4762 |
| 1.0827 | 32.0 | 192 | 1.0695 | 0.5 |
| 1.0827 | 33.0 | 198 | 1.2349 | 0.4762 |
| 1.1051 | 34.0 | 204 | 1.1006 | 0.5238 |
| 1.0196 | 35.0 | 210 | 1.0684 | 0.5476 |
| 1.0196 | 36.0 | 216 | 0.9937 | 0.5238 |
| 1.0022 | 37.0 | 222 | 1.2962 | 0.5238 |
| 1.0022 | 38.0 | 228 | 1.0911 | 0.5476 |
| 0.9974 | 39.0 | 234 | 1.1681 | 0.5 |
| 0.9742 | 40.0 | 240 | 1.3925 | 0.5476 |
| 0.9742 | 41.0 | 246 | 1.2876 | 0.5714 |
| 0.9338 | 42.0 | 252 | 1.2820 | 0.5714 |
| 0.9338 | 43.0 | 258 | 1.2820 | 0.5714 |
| 0.8995 | 44.0 | 264 | 1.2820 | 0.5714 |
| 0.9368 | 45.0 | 270 | 1.2820 | 0.5714 |
| 0.9368 | 46.0 | 276 | 1.2820 | 0.5714 |
| 0.9236 | 47.0 | 282 | 1.2820 | 0.5714 |
| 0.9236 | 48.0 | 288 | 1.2820 | 0.5714 |
| 0.929 | 49.0 | 294 | 1.2820 | 0.5714 |
| 0.9198 | 50.0 | 300 | 1.2820 | 0.5714 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0