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_sgd_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: 0.2222222222222222
hushem_1x_deit_base_sgd_001_fold1
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: 1.4169
- Accuracy: 0.2222
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 | 1.5144 | 0.1333 |
| 1.4099 | 2.0 | 12 | 1.5058 | 0.1333 |
| 1.4099 | 3.0 | 18 | 1.4975 | 0.1333 |
| 1.3953 | 4.0 | 24 | 1.4914 | 0.1333 |
| 1.3839 | 5.0 | 30 | 1.4843 | 0.1556 |
| 1.3839 | 6.0 | 36 | 1.4779 | 0.1778 |
| 1.3707 | 7.0 | 42 | 1.4724 | 0.1778 |
| 1.3707 | 8.0 | 48 | 1.4679 | 0.1778 |
| 1.3722 | 9.0 | 54 | 1.4633 | 0.1778 |
| 1.3434 | 10.0 | 60 | 1.4589 | 0.1778 |
| 1.3434 | 11.0 | 66 | 1.4552 | 0.2 |
| 1.3467 | 12.0 | 72 | 1.4521 | 0.2 |
| 1.3467 | 13.0 | 78 | 1.4488 | 0.2 |
| 1.3313 | 14.0 | 84 | 1.4460 | 0.2 |
| 1.33 | 15.0 | 90 | 1.4434 | 0.2 |
| 1.33 | 16.0 | 96 | 1.4413 | 0.2 |
| 1.325 | 17.0 | 102 | 1.4392 | 0.2 |
| 1.325 | 18.0 | 108 | 1.4371 | 0.2 |
| 1.3231 | 19.0 | 114 | 1.4349 | 0.2222 |
| 1.3131 | 20.0 | 120 | 1.4330 | 0.2222 |
| 1.3131 | 21.0 | 126 | 1.4314 | 0.2444 |
| 1.3095 | 22.0 | 132 | 1.4300 | 0.2444 |
| 1.3095 | 23.0 | 138 | 1.4284 | 0.2444 |
| 1.3181 | 24.0 | 144 | 1.4271 | 0.2444 |
| 1.2959 | 25.0 | 150 | 1.4260 | 0.2222 |
| 1.2959 | 26.0 | 156 | 1.4247 | 0.2222 |
| 1.2924 | 27.0 | 162 | 1.4239 | 0.2222 |
| 1.2924 | 28.0 | 168 | 1.4230 | 0.2222 |
| 1.2867 | 29.0 | 174 | 1.4221 | 0.2222 |
| 1.2887 | 30.0 | 180 | 1.4212 | 0.2222 |
| 1.2887 | 31.0 | 186 | 1.4204 | 0.2222 |
| 1.2851 | 32.0 | 192 | 1.4198 | 0.2222 |
| 1.2851 | 33.0 | 198 | 1.4193 | 0.2222 |
| 1.2896 | 34.0 | 204 | 1.4187 | 0.2222 |
| 1.2742 | 35.0 | 210 | 1.4183 | 0.2222 |
| 1.2742 | 36.0 | 216 | 1.4179 | 0.2222 |
| 1.2726 | 37.0 | 222 | 1.4176 | 0.2222 |
| 1.2726 | 38.0 | 228 | 1.4173 | 0.2222 |
| 1.2881 | 39.0 | 234 | 1.4171 | 0.2222 |
| 1.2721 | 40.0 | 240 | 1.4170 | 0.2222 |
| 1.2721 | 41.0 | 246 | 1.4169 | 0.2222 |
| 1.2788 | 42.0 | 252 | 1.4169 | 0.2222 |
| 1.2788 | 43.0 | 258 | 1.4169 | 0.2222 |
| 1.2737 | 44.0 | 264 | 1.4169 | 0.2222 |
| 1.2763 | 45.0 | 270 | 1.4169 | 0.2222 |
| 1.2763 | 46.0 | 276 | 1.4169 | 0.2222 |
| 1.2804 | 47.0 | 282 | 1.4169 | 0.2222 |
| 1.2804 | 48.0 | 288 | 1.4169 | 0.2222 |
| 1.2603 | 49.0 | 294 | 1.4169 | 0.2222 |
| 1.275 | 50.0 | 300 | 1.4169 | 0.2222 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0