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_adamax_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: 0.4666666666666667
hushem_1x_deit_small_adamax_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: 2.0215
- Accuracy: 0.4667
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 | 2.2870 | 0.2444 |
| 2.1668 | 2.0 | 12 | 1.4669 | 0.2444 |
| 2.1668 | 3.0 | 18 | 1.4980 | 0.2444 |
| 1.4102 | 4.0 | 24 | 1.4751 | 0.2444 |
| 1.4394 | 5.0 | 30 | 1.4286 | 0.2444 |
| 1.4394 | 6.0 | 36 | 1.6019 | 0.2444 |
| 1.3171 | 7.0 | 42 | 1.7291 | 0.2222 |
| 1.3171 | 8.0 | 48 | 1.5314 | 0.3556 |
| 1.2906 | 9.0 | 54 | 1.7281 | 0.2667 |
| 1.2151 | 10.0 | 60 | 1.6012 | 0.2444 |
| 1.2151 | 11.0 | 66 | 1.5621 | 0.4444 |
| 1.1016 | 12.0 | 72 | 1.5069 | 0.2 |
| 1.1016 | 13.0 | 78 | 1.5452 | 0.4222 |
| 1.1085 | 14.0 | 84 | 1.5457 | 0.2889 |
| 0.9838 | 15.0 | 90 | 1.7131 | 0.4 |
| 0.9838 | 16.0 | 96 | 1.9947 | 0.2889 |
| 1.003 | 17.0 | 102 | 1.7538 | 0.4222 |
| 1.003 | 18.0 | 108 | 1.3632 | 0.4444 |
| 0.846 | 19.0 | 114 | 1.7633 | 0.4 |
| 0.7432 | 20.0 | 120 | 1.5259 | 0.4222 |
| 0.7432 | 21.0 | 126 | 1.6982 | 0.4 |
| 0.8111 | 22.0 | 132 | 1.4722 | 0.4 |
| 0.8111 | 23.0 | 138 | 1.5772 | 0.4222 |
| 0.6268 | 24.0 | 144 | 1.6621 | 0.4222 |
| 0.5956 | 25.0 | 150 | 2.2283 | 0.4 |
| 0.5956 | 26.0 | 156 | 1.5965 | 0.4667 |
| 0.863 | 27.0 | 162 | 2.0067 | 0.4 |
| 0.863 | 28.0 | 168 | 2.2609 | 0.3778 |
| 0.575 | 29.0 | 174 | 1.7339 | 0.4222 |
| 0.3505 | 30.0 | 180 | 1.6059 | 0.3778 |
| 0.3505 | 31.0 | 186 | 1.7578 | 0.4444 |
| 0.3884 | 32.0 | 192 | 1.8785 | 0.4444 |
| 0.3884 | 33.0 | 198 | 1.5952 | 0.4222 |
| 0.3742 | 34.0 | 204 | 1.9834 | 0.4444 |
| 0.3113 | 35.0 | 210 | 1.8134 | 0.4222 |
| 0.3113 | 36.0 | 216 | 2.1491 | 0.4 |
| 0.4478 | 37.0 | 222 | 1.9419 | 0.4667 |
| 0.4478 | 38.0 | 228 | 1.8426 | 0.4444 |
| 0.1746 | 39.0 | 234 | 1.9349 | 0.4222 |
| 0.1737 | 40.0 | 240 | 2.0085 | 0.4667 |
| 0.1737 | 41.0 | 246 | 2.0238 | 0.4667 |
| 0.1448 | 42.0 | 252 | 2.0215 | 0.4667 |
| 0.1448 | 43.0 | 258 | 2.0215 | 0.4667 |
| 0.1495 | 44.0 | 264 | 2.0215 | 0.4667 |
| 0.1326 | 45.0 | 270 | 2.0215 | 0.4667 |
| 0.1326 | 46.0 | 276 | 2.0215 | 0.4667 |
| 0.1487 | 47.0 | 282 | 2.0215 | 0.4667 |
| 0.1487 | 48.0 | 288 | 2.0215 | 0.4667 |
| 0.1112 | 49.0 | 294 | 2.0215 | 0.4667 |
| 0.1501 | 50.0 | 300 | 2.0215 | 0.4667 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1