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_0001_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: 0.2857142857142857
hushem_1x_deit_tiny_sgd_0001_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: 1.5092
- Accuracy: 0.2857
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 | 1.6866 | 0.2857 |
| 1.7029 | 2.0 | 12 | 1.6755 | 0.2857 |
| 1.7029 | 3.0 | 18 | 1.6648 | 0.2857 |
| 1.6819 | 4.0 | 24 | 1.6543 | 0.2857 |
| 1.7084 | 5.0 | 30 | 1.6452 | 0.2857 |
| 1.7084 | 6.0 | 36 | 1.6365 | 0.2857 |
| 1.661 | 7.0 | 42 | 1.6277 | 0.2857 |
| 1.661 | 8.0 | 48 | 1.6195 | 0.2857 |
| 1.6506 | 9.0 | 54 | 1.6113 | 0.2857 |
| 1.6321 | 10.0 | 60 | 1.6035 | 0.2857 |
| 1.6321 | 11.0 | 66 | 1.5969 | 0.2857 |
| 1.605 | 12.0 | 72 | 1.5900 | 0.2857 |
| 1.605 | 13.0 | 78 | 1.5837 | 0.2857 |
| 1.6205 | 14.0 | 84 | 1.5775 | 0.2857 |
| 1.6128 | 15.0 | 90 | 1.5717 | 0.2857 |
| 1.6128 | 16.0 | 96 | 1.5663 | 0.2857 |
| 1.5818 | 17.0 | 102 | 1.5613 | 0.2857 |
| 1.5818 | 18.0 | 108 | 1.5566 | 0.2857 |
| 1.6012 | 19.0 | 114 | 1.5522 | 0.2857 |
| 1.6068 | 20.0 | 120 | 1.5482 | 0.2857 |
| 1.6068 | 21.0 | 126 | 1.5443 | 0.2857 |
| 1.5674 | 22.0 | 132 | 1.5409 | 0.2857 |
| 1.5674 | 23.0 | 138 | 1.5376 | 0.2857 |
| 1.565 | 24.0 | 144 | 1.5344 | 0.2857 |
| 1.5842 | 25.0 | 150 | 1.5314 | 0.2857 |
| 1.5842 | 26.0 | 156 | 1.5286 | 0.2857 |
| 1.5593 | 27.0 | 162 | 1.5260 | 0.2857 |
| 1.5593 | 28.0 | 168 | 1.5236 | 0.2857 |
| 1.5824 | 29.0 | 174 | 1.5216 | 0.2857 |
| 1.537 | 30.0 | 180 | 1.5196 | 0.2857 |
| 1.537 | 31.0 | 186 | 1.5181 | 0.2857 |
| 1.5437 | 32.0 | 192 | 1.5165 | 0.2857 |
| 1.5437 | 33.0 | 198 | 1.5150 | 0.2857 |
| 1.5369 | 34.0 | 204 | 1.5137 | 0.2857 |
| 1.5371 | 35.0 | 210 | 1.5125 | 0.2857 |
| 1.5371 | 36.0 | 216 | 1.5116 | 0.2857 |
| 1.5229 | 37.0 | 222 | 1.5109 | 0.2857 |
| 1.5229 | 38.0 | 228 | 1.5102 | 0.2857 |
| 1.5623 | 39.0 | 234 | 1.5097 | 0.2857 |
| 1.5343 | 40.0 | 240 | 1.5094 | 0.2857 |
| 1.5343 | 41.0 | 246 | 1.5093 | 0.2857 |
| 1.5211 | 42.0 | 252 | 1.5092 | 0.2857 |
| 1.5211 | 43.0 | 258 | 1.5092 | 0.2857 |
| 1.5618 | 44.0 | 264 | 1.5092 | 0.2857 |
| 1.5309 | 45.0 | 270 | 1.5092 | 0.2857 |
| 1.5309 | 46.0 | 276 | 1.5092 | 0.2857 |
| 1.5362 | 47.0 | 282 | 1.5092 | 0.2857 |
| 1.5362 | 48.0 | 288 | 1.5092 | 0.2857 |
| 1.5728 | 49.0 | 294 | 1.5092 | 0.2857 |
| 1.5244 | 50.0 | 300 | 1.5092 | 0.2857 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1