metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_small_rms_001_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: 0.35555555555555557
hushem_1x_deit_small_rms_001_fold1
This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.5587
- 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 | 5.6616 | 0.2444 |
| 4.5403 | 2.0 | 12 | 1.9139 | 0.2444 |
| 4.5403 | 3.0 | 18 | 1.7372 | 0.2444 |
| 1.8724 | 4.0 | 24 | 1.4323 | 0.2667 |
| 1.5505 | 5.0 | 30 | 1.5541 | 0.2444 |
| 1.5505 | 6.0 | 36 | 1.5305 | 0.2444 |
| 1.4992 | 7.0 | 42 | 1.5286 | 0.2444 |
| 1.4992 | 8.0 | 48 | 1.5617 | 0.2444 |
| 1.4899 | 9.0 | 54 | 1.4717 | 0.2444 |
| 1.4501 | 10.0 | 60 | 1.4440 | 0.2444 |
| 1.4501 | 11.0 | 66 | 1.4155 | 0.2667 |
| 1.4052 | 12.0 | 72 | 1.3606 | 0.2444 |
| 1.4052 | 13.0 | 78 | 1.4215 | 0.3333 |
| 1.4555 | 14.0 | 84 | 1.3356 | 0.3333 |
| 1.4209 | 15.0 | 90 | 1.4688 | 0.2667 |
| 1.4209 | 16.0 | 96 | 1.2956 | 0.4444 |
| 1.4079 | 17.0 | 102 | 1.4012 | 0.2444 |
| 1.4079 | 18.0 | 108 | 1.4817 | 0.2444 |
| 1.4101 | 19.0 | 114 | 1.4296 | 0.2667 |
| 1.6129 | 20.0 | 120 | 1.5601 | 0.2444 |
| 1.6129 | 21.0 | 126 | 1.8216 | 0.2667 |
| 1.5349 | 22.0 | 132 | 1.6109 | 0.2667 |
| 1.5349 | 23.0 | 138 | 1.6663 | 0.2444 |
| 1.4443 | 24.0 | 144 | 1.4166 | 0.2444 |
| 1.3949 | 25.0 | 150 | 1.5159 | 0.2444 |
| 1.3949 | 26.0 | 156 | 1.5557 | 0.2444 |
| 1.2549 | 27.0 | 162 | 1.2710 | 0.3333 |
| 1.2549 | 28.0 | 168 | 1.4661 | 0.3333 |
| 1.2756 | 29.0 | 174 | 1.3759 | 0.3111 |
| 1.2244 | 30.0 | 180 | 1.3243 | 0.4222 |
| 1.2244 | 31.0 | 186 | 1.1877 | 0.4222 |
| 1.1482 | 32.0 | 192 | 1.1943 | 0.4667 |
| 1.1482 | 33.0 | 198 | 1.3644 | 0.3111 |
| 1.0904 | 34.0 | 204 | 1.3812 | 0.3778 |
| 1.051 | 35.0 | 210 | 1.3131 | 0.4444 |
| 1.051 | 36.0 | 216 | 1.7518 | 0.2667 |
| 1.0583 | 37.0 | 222 | 1.8440 | 0.3556 |
| 1.0583 | 38.0 | 228 | 1.7450 | 0.2889 |
| 0.8766 | 39.0 | 234 | 1.5767 | 0.3556 |
| 0.9084 | 40.0 | 240 | 1.5052 | 0.3778 |
| 0.9084 | 41.0 | 246 | 1.5534 | 0.3556 |
| 0.8553 | 42.0 | 252 | 1.5587 | 0.3556 |
| 0.8553 | 43.0 | 258 | 1.5587 | 0.3556 |
| 0.8404 | 44.0 | 264 | 1.5587 | 0.3556 |
| 0.8432 | 45.0 | 270 | 1.5587 | 0.3556 |
| 0.8432 | 46.0 | 276 | 1.5587 | 0.3556 |
| 0.8133 | 47.0 | 282 | 1.5587 | 0.3556 |
| 0.8133 | 48.0 | 288 | 1.5587 | 0.3556 |
| 0.8467 | 49.0 | 294 | 1.5587 | 0.3556 |
| 0.8396 | 50.0 | 300 | 1.5587 | 0.3556 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1