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_lr001_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: 0.27906976744186046
hushem_1x_deit_tiny_rms_lr001_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: 1.7042
- Accuracy: 0.2791
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 | 3.1061 | 0.2326 |
| 4.0184 | 2.0 | 12 | 1.7666 | 0.2558 |
| 4.0184 | 3.0 | 18 | 1.6279 | 0.2558 |
| 1.7385 | 4.0 | 24 | 1.9636 | 0.2558 |
| 1.583 | 5.0 | 30 | 1.6503 | 0.2558 |
| 1.583 | 6.0 | 36 | 1.4630 | 0.2326 |
| 1.4859 | 7.0 | 42 | 3.2936 | 0.2326 |
| 1.4859 | 8.0 | 48 | 2.0073 | 0.2558 |
| 2.0303 | 9.0 | 54 | 1.4859 | 0.2326 |
| 1.4062 | 10.0 | 60 | 1.6529 | 0.2326 |
| 1.4062 | 11.0 | 66 | 1.4259 | 0.2791 |
| 1.359 | 12.0 | 72 | 1.3892 | 0.2558 |
| 1.359 | 13.0 | 78 | 1.4650 | 0.3023 |
| 1.3464 | 14.0 | 84 | 1.4368 | 0.2558 |
| 1.262 | 15.0 | 90 | 1.4241 | 0.2558 |
| 1.262 | 16.0 | 96 | 1.6562 | 0.3023 |
| 1.2521 | 17.0 | 102 | 1.3729 | 0.3023 |
| 1.2521 | 18.0 | 108 | 1.5241 | 0.2093 |
| 1.2212 | 19.0 | 114 | 1.5032 | 0.3023 |
| 1.1882 | 20.0 | 120 | 1.4178 | 0.2558 |
| 1.1882 | 21.0 | 126 | 1.8156 | 0.3023 |
| 1.1382 | 22.0 | 132 | 1.5280 | 0.2558 |
| 1.1382 | 23.0 | 138 | 1.5037 | 0.2326 |
| 1.0802 | 24.0 | 144 | 1.5058 | 0.3488 |
| 1.1083 | 25.0 | 150 | 1.5421 | 0.2791 |
| 1.1083 | 26.0 | 156 | 1.5398 | 0.2558 |
| 1.0555 | 27.0 | 162 | 1.8560 | 0.2791 |
| 1.0555 | 28.0 | 168 | 1.9193 | 0.2558 |
| 1.0051 | 29.0 | 174 | 1.5934 | 0.3256 |
| 0.958 | 30.0 | 180 | 1.6481 | 0.2791 |
| 0.958 | 31.0 | 186 | 1.5950 | 0.2791 |
| 0.9855 | 32.0 | 192 | 1.5539 | 0.2558 |
| 0.9855 | 33.0 | 198 | 1.6644 | 0.2791 |
| 0.9482 | 34.0 | 204 | 1.6743 | 0.2326 |
| 0.9401 | 35.0 | 210 | 1.6352 | 0.3023 |
| 0.9401 | 36.0 | 216 | 1.6896 | 0.2791 |
| 0.9225 | 37.0 | 222 | 1.7369 | 0.2326 |
| 0.9225 | 38.0 | 228 | 1.6916 | 0.2558 |
| 0.8891 | 39.0 | 234 | 1.6919 | 0.2791 |
| 0.8732 | 40.0 | 240 | 1.7104 | 0.2791 |
| 0.8732 | 41.0 | 246 | 1.7028 | 0.2791 |
| 0.8715 | 42.0 | 252 | 1.7042 | 0.2791 |
| 0.8715 | 43.0 | 258 | 1.7042 | 0.2791 |
| 0.8826 | 44.0 | 264 | 1.7042 | 0.2791 |
| 0.8986 | 45.0 | 270 | 1.7042 | 0.2791 |
| 0.8986 | 46.0 | 276 | 1.7042 | 0.2791 |
| 0.8589 | 47.0 | 282 | 1.7042 | 0.2791 |
| 0.8589 | 48.0 | 288 | 1.7042 | 0.2791 |
| 0.9236 | 49.0 | 294 | 1.7042 | 0.2791 |
| 0.8539 | 50.0 | 300 | 1.7042 | 0.2791 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1