metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_rms_001_fold3
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: 0.4186046511627907
hushem_1x_deit_tiny_rms_001_fold3
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1536
- Accuracy: 0.4186
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 | 3.8148 | 0.2558 |
| 4.0682 | 2.0 | 12 | 1.5106 | 0.2558 |
| 4.0682 | 3.0 | 18 | 2.1015 | 0.2558 |
| 1.8697 | 4.0 | 24 | 2.1521 | 0.2558 |
| 1.6204 | 5.0 | 30 | 2.0540 | 0.2558 |
| 1.6204 | 6.0 | 36 | 1.4487 | 0.2558 |
| 1.5557 | 7.0 | 42 | 1.5322 | 0.2326 |
| 1.5557 | 8.0 | 48 | 1.6480 | 0.2558 |
| 1.5276 | 9.0 | 54 | 1.5085 | 0.2558 |
| 1.4446 | 10.0 | 60 | 1.3921 | 0.2558 |
| 1.4446 | 11.0 | 66 | 1.5703 | 0.2558 |
| 1.4728 | 12.0 | 72 | 1.3608 | 0.2791 |
| 1.4728 | 13.0 | 78 | 1.4250 | 0.3488 |
| 1.3652 | 14.0 | 84 | 1.4495 | 0.2558 |
| 1.3593 | 15.0 | 90 | 1.4182 | 0.3023 |
| 1.3593 | 16.0 | 96 | 1.5418 | 0.3023 |
| 1.2943 | 17.0 | 102 | 1.4454 | 0.3256 |
| 1.2943 | 18.0 | 108 | 1.5941 | 0.3721 |
| 1.2915 | 19.0 | 114 | 1.4889 | 0.2558 |
| 1.2591 | 20.0 | 120 | 1.3804 | 0.3488 |
| 1.2591 | 21.0 | 126 | 1.8125 | 0.2558 |
| 1.2263 | 22.0 | 132 | 1.4098 | 0.3023 |
| 1.2263 | 23.0 | 138 | 1.4818 | 0.2558 |
| 1.1885 | 24.0 | 144 | 1.4257 | 0.3721 |
| 1.1814 | 25.0 | 150 | 1.4317 | 0.3023 |
| 1.1814 | 26.0 | 156 | 1.3854 | 0.3488 |
| 1.1163 | 27.0 | 162 | 1.9054 | 0.3256 |
| 1.1163 | 28.0 | 168 | 1.3109 | 0.3488 |
| 1.0609 | 29.0 | 174 | 1.3896 | 0.3488 |
| 1.1038 | 30.0 | 180 | 1.3466 | 0.3256 |
| 1.1038 | 31.0 | 186 | 1.3101 | 0.3256 |
| 1.0099 | 32.0 | 192 | 1.2865 | 0.3721 |
| 1.0099 | 33.0 | 198 | 1.2846 | 0.3721 |
| 1.0297 | 34.0 | 204 | 1.2587 | 0.4186 |
| 0.964 | 35.0 | 210 | 1.2832 | 0.3953 |
| 0.964 | 36.0 | 216 | 1.1929 | 0.3721 |
| 0.9335 | 37.0 | 222 | 1.2162 | 0.3953 |
| 0.9335 | 38.0 | 228 | 1.1906 | 0.4419 |
| 0.8668 | 39.0 | 234 | 1.1859 | 0.4186 |
| 0.8296 | 40.0 | 240 | 1.1516 | 0.4884 |
| 0.8296 | 41.0 | 246 | 1.1577 | 0.4651 |
| 0.8332 | 42.0 | 252 | 1.1536 | 0.4186 |
| 0.8332 | 43.0 | 258 | 1.1536 | 0.4186 |
| 0.8289 | 44.0 | 264 | 1.1536 | 0.4186 |
| 0.8217 | 45.0 | 270 | 1.1536 | 0.4186 |
| 0.8217 | 46.0 | 276 | 1.1536 | 0.4186 |
| 0.8205 | 47.0 | 282 | 1.1536 | 0.4186 |
| 0.8205 | 48.0 | 288 | 1.1536 | 0.4186 |
| 0.8548 | 49.0 | 294 | 1.1536 | 0.4186 |
| 0.8042 | 50.0 | 300 | 1.1536 | 0.4186 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1