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_sgd_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: 0.3333333333333333
hushem_1x_deit_small_sgd_001_fold4
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: 1.3002
- Accuracy: 0.3333
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 | 1.4504 | 0.2857 |
| 1.4996 | 2.0 | 12 | 1.4256 | 0.2619 |
| 1.4996 | 3.0 | 18 | 1.4065 | 0.3095 |
| 1.4661 | 4.0 | 24 | 1.3909 | 0.3333 |
| 1.4137 | 5.0 | 30 | 1.3815 | 0.3333 |
| 1.4137 | 6.0 | 36 | 1.3736 | 0.3810 |
| 1.3923 | 7.0 | 42 | 1.3662 | 0.3571 |
| 1.3923 | 8.0 | 48 | 1.3602 | 0.3095 |
| 1.3511 | 9.0 | 54 | 1.3552 | 0.3333 |
| 1.3471 | 10.0 | 60 | 1.3505 | 0.3333 |
| 1.3471 | 11.0 | 66 | 1.3464 | 0.3333 |
| 1.3212 | 12.0 | 72 | 1.3425 | 0.3333 |
| 1.3212 | 13.0 | 78 | 1.3391 | 0.3333 |
| 1.3151 | 14.0 | 84 | 1.3358 | 0.3333 |
| 1.2949 | 15.0 | 90 | 1.3328 | 0.3333 |
| 1.2949 | 16.0 | 96 | 1.3296 | 0.3333 |
| 1.282 | 17.0 | 102 | 1.3270 | 0.3333 |
| 1.282 | 18.0 | 108 | 1.3243 | 0.3333 |
| 1.2637 | 19.0 | 114 | 1.3223 | 0.3333 |
| 1.2828 | 20.0 | 120 | 1.3203 | 0.3333 |
| 1.2828 | 21.0 | 126 | 1.3182 | 0.3333 |
| 1.2384 | 22.0 | 132 | 1.3165 | 0.3333 |
| 1.2384 | 23.0 | 138 | 1.3149 | 0.3333 |
| 1.2419 | 24.0 | 144 | 1.3133 | 0.3333 |
| 1.2404 | 25.0 | 150 | 1.3117 | 0.3571 |
| 1.2404 | 26.0 | 156 | 1.3102 | 0.3571 |
| 1.2294 | 27.0 | 162 | 1.3091 | 0.3571 |
| 1.2294 | 28.0 | 168 | 1.3080 | 0.3571 |
| 1.2327 | 29.0 | 174 | 1.3070 | 0.3571 |
| 1.2115 | 30.0 | 180 | 1.3061 | 0.3571 |
| 1.2115 | 31.0 | 186 | 1.3052 | 0.3333 |
| 1.2091 | 32.0 | 192 | 1.3043 | 0.3333 |
| 1.2091 | 33.0 | 198 | 1.3036 | 0.3333 |
| 1.2111 | 34.0 | 204 | 1.3028 | 0.3333 |
| 1.2001 | 35.0 | 210 | 1.3022 | 0.3333 |
| 1.2001 | 36.0 | 216 | 1.3016 | 0.3333 |
| 1.2048 | 37.0 | 222 | 1.3012 | 0.3333 |
| 1.2048 | 38.0 | 228 | 1.3009 | 0.3333 |
| 1.1981 | 39.0 | 234 | 1.3006 | 0.3333 |
| 1.1973 | 40.0 | 240 | 1.3004 | 0.3333 |
| 1.1973 | 41.0 | 246 | 1.3003 | 0.3333 |
| 1.2009 | 42.0 | 252 | 1.3002 | 0.3333 |
| 1.2009 | 43.0 | 258 | 1.3002 | 0.3333 |
| 1.1848 | 44.0 | 264 | 1.3002 | 0.3333 |
| 1.2 | 45.0 | 270 | 1.3002 | 0.3333 |
| 1.2 | 46.0 | 276 | 1.3002 | 0.3333 |
| 1.2026 | 47.0 | 282 | 1.3002 | 0.3333 |
| 1.2026 | 48.0 | 288 | 1.3002 | 0.3333 |
| 1.1883 | 49.0 | 294 | 1.3002 | 0.3333 |
| 1.2097 | 50.0 | 300 | 1.3002 | 0.3333 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1