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_0001_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: 0.7555555555555555
hushem_1x_deit_base_adamax_0001_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: 1.0735
- Accuracy: 0.7556
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 | 1.2850 | 0.3333 |
| 1.0598 | 2.0 | 12 | 0.9334 | 0.6889 |
| 1.0598 | 3.0 | 18 | 0.8053 | 0.7333 |
| 0.3175 | 4.0 | 24 | 0.8711 | 0.6444 |
| 0.0445 | 5.0 | 30 | 0.8608 | 0.7556 |
| 0.0445 | 6.0 | 36 | 0.7787 | 0.7778 |
| 0.0064 | 7.0 | 42 | 0.8229 | 0.7111 |
| 0.0064 | 8.0 | 48 | 0.9560 | 0.6667 |
| 0.0019 | 9.0 | 54 | 1.0123 | 0.7111 |
| 0.001 | 10.0 | 60 | 1.0574 | 0.7111 |
| 0.001 | 11.0 | 66 | 1.0683 | 0.7111 |
| 0.0007 | 12.0 | 72 | 1.0663 | 0.7111 |
| 0.0007 | 13.0 | 78 | 1.0586 | 0.7111 |
| 0.0005 | 14.0 | 84 | 1.0513 | 0.7333 |
| 0.0005 | 15.0 | 90 | 1.0471 | 0.7333 |
| 0.0005 | 16.0 | 96 | 1.0473 | 0.7333 |
| 0.0004 | 17.0 | 102 | 1.0477 | 0.7333 |
| 0.0004 | 18.0 | 108 | 1.0472 | 0.7333 |
| 0.0004 | 19.0 | 114 | 1.0473 | 0.7333 |
| 0.0004 | 20.0 | 120 | 1.0490 | 0.7556 |
| 0.0004 | 21.0 | 126 | 1.0517 | 0.7556 |
| 0.0004 | 22.0 | 132 | 1.0538 | 0.7556 |
| 0.0004 | 23.0 | 138 | 1.0557 | 0.7556 |
| 0.0003 | 24.0 | 144 | 1.0576 | 0.7556 |
| 0.0003 | 25.0 | 150 | 1.0597 | 0.7556 |
| 0.0003 | 26.0 | 156 | 1.0622 | 0.7556 |
| 0.0003 | 27.0 | 162 | 1.0623 | 0.7556 |
| 0.0003 | 28.0 | 168 | 1.0636 | 0.7556 |
| 0.0003 | 29.0 | 174 | 1.0651 | 0.7556 |
| 0.0003 | 30.0 | 180 | 1.0659 | 0.7556 |
| 0.0003 | 31.0 | 186 | 1.0671 | 0.7556 |
| 0.0003 | 32.0 | 192 | 1.0678 | 0.7556 |
| 0.0003 | 33.0 | 198 | 1.0692 | 0.7556 |
| 0.0003 | 34.0 | 204 | 1.0702 | 0.7556 |
| 0.0003 | 35.0 | 210 | 1.0706 | 0.7556 |
| 0.0003 | 36.0 | 216 | 1.0707 | 0.7556 |
| 0.0003 | 37.0 | 222 | 1.0711 | 0.7556 |
| 0.0003 | 38.0 | 228 | 1.0722 | 0.7556 |
| 0.0003 | 39.0 | 234 | 1.0729 | 0.7556 |
| 0.0003 | 40.0 | 240 | 1.0733 | 0.7556 |
| 0.0003 | 41.0 | 246 | 1.0735 | 0.7556 |
| 0.0003 | 42.0 | 252 | 1.0735 | 0.7556 |
| 0.0003 | 43.0 | 258 | 1.0735 | 0.7556 |
| 0.0003 | 44.0 | 264 | 1.0735 | 0.7556 |
| 0.0003 | 45.0 | 270 | 1.0735 | 0.7556 |
| 0.0003 | 46.0 | 276 | 1.0735 | 0.7556 |
| 0.0003 | 47.0 | 282 | 1.0735 | 0.7556 |
| 0.0003 | 48.0 | 288 | 1.0735 | 0.7556 |
| 0.0003 | 49.0 | 294 | 1.0735 | 0.7556 |
| 0.0003 | 50.0 | 300 | 1.0735 | 0.7556 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1