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_adamax_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: 0.5952380952380952
hushem_1x_deit_base_adamax_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: 2.6471
- Accuracy: 0.5952
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 | 1.4889 | 0.2381 |
| 1.6928 | 2.0 | 12 | 1.4102 | 0.2381 |
| 1.6928 | 3.0 | 18 | 1.2949 | 0.4048 |
| 1.4466 | 4.0 | 24 | 1.1224 | 0.4762 |
| 1.3026 | 5.0 | 30 | 1.3079 | 0.3333 |
| 1.3026 | 6.0 | 36 | 1.0368 | 0.6190 |
| 1.2798 | 7.0 | 42 | 1.2143 | 0.3571 |
| 1.2798 | 8.0 | 48 | 1.0732 | 0.5 |
| 1.1914 | 9.0 | 54 | 1.0366 | 0.5476 |
| 1.2164 | 10.0 | 60 | 1.0675 | 0.5 |
| 1.2164 | 11.0 | 66 | 1.0841 | 0.4762 |
| 1.2177 | 12.0 | 72 | 1.1092 | 0.5952 |
| 1.2177 | 13.0 | 78 | 0.9871 | 0.5238 |
| 1.183 | 14.0 | 84 | 1.1380 | 0.4762 |
| 1.2146 | 15.0 | 90 | 1.1128 | 0.5 |
| 1.2146 | 16.0 | 96 | 0.9957 | 0.5952 |
| 1.1103 | 17.0 | 102 | 1.0192 | 0.5952 |
| 1.1103 | 18.0 | 108 | 1.1751 | 0.5 |
| 1.0656 | 19.0 | 114 | 1.1301 | 0.5 |
| 1.047 | 20.0 | 120 | 1.1327 | 0.4048 |
| 1.047 | 21.0 | 126 | 1.2359 | 0.4762 |
| 0.8853 | 22.0 | 132 | 1.1524 | 0.5952 |
| 0.8853 | 23.0 | 138 | 1.9551 | 0.3095 |
| 0.7611 | 24.0 | 144 | 1.3513 | 0.5 |
| 0.7727 | 25.0 | 150 | 1.6490 | 0.5476 |
| 0.7727 | 26.0 | 156 | 1.0702 | 0.4048 |
| 0.8546 | 27.0 | 162 | 1.7107 | 0.3333 |
| 0.8546 | 28.0 | 168 | 1.3302 | 0.4286 |
| 0.695 | 29.0 | 174 | 1.1947 | 0.5714 |
| 0.4593 | 30.0 | 180 | 1.8330 | 0.4762 |
| 0.4593 | 31.0 | 186 | 1.6031 | 0.5952 |
| 0.2978 | 32.0 | 192 | 2.1238 | 0.6190 |
| 0.2978 | 33.0 | 198 | 2.3897 | 0.5476 |
| 0.2625 | 34.0 | 204 | 2.1147 | 0.6190 |
| 0.1062 | 35.0 | 210 | 2.6950 | 0.5 |
| 0.1062 | 36.0 | 216 | 2.5016 | 0.6190 |
| 0.0682 | 37.0 | 222 | 2.6327 | 0.5476 |
| 0.0682 | 38.0 | 228 | 2.5000 | 0.5714 |
| 0.0309 | 39.0 | 234 | 2.4431 | 0.6190 |
| 0.019 | 40.0 | 240 | 2.6997 | 0.5714 |
| 0.019 | 41.0 | 246 | 2.6710 | 0.5952 |
| 0.0078 | 42.0 | 252 | 2.6471 | 0.5952 |
| 0.0078 | 43.0 | 258 | 2.6471 | 0.5952 |
| 0.0071 | 44.0 | 264 | 2.6471 | 0.5952 |
| 0.0054 | 45.0 | 270 | 2.6471 | 0.5952 |
| 0.0054 | 46.0 | 276 | 2.6471 | 0.5952 |
| 0.0076 | 47.0 | 282 | 2.6471 | 0.5952 |
| 0.0076 | 48.0 | 288 | 2.6471 | 0.5952 |
| 0.0053 | 49.0 | 294 | 2.6471 | 0.5952 |
| 0.0059 | 50.0 | 300 | 2.6471 | 0.5952 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1