metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_conflu_deneme_f1
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: 0.4222222222222222
hushem_conflu_deneme_f1
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: 4.1726
- Accuracy: 0.4222
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 | 1.4791 | 0.3333 |
| 2.0372 | 2.0 | 12 | 1.3991 | 0.2444 |
| 2.0372 | 3.0 | 18 | 1.9327 | 0.2444 |
| 1.2524 | 4.0 | 24 | 1.4584 | 0.3556 |
| 1.1547 | 5.0 | 30 | 1.3317 | 0.3556 |
| 1.1547 | 6.0 | 36 | 1.9319 | 0.3333 |
| 0.8748 | 7.0 | 42 | 1.3603 | 0.4222 |
| 0.8748 | 8.0 | 48 | 1.0979 | 0.5333 |
| 0.8902 | 9.0 | 54 | 1.9103 | 0.4222 |
| 0.6653 | 10.0 | 60 | 2.0004 | 0.3778 |
| 0.6653 | 11.0 | 66 | 2.0962 | 0.4 |
| 0.5253 | 12.0 | 72 | 1.2246 | 0.5111 |
| 0.5253 | 13.0 | 78 | 1.6731 | 0.4889 |
| 0.5223 | 14.0 | 84 | 2.1516 | 0.4 |
| 0.2968 | 15.0 | 90 | 2.5065 | 0.4 |
| 0.2968 | 16.0 | 96 | 2.0657 | 0.4444 |
| 0.4394 | 17.0 | 102 | 1.5876 | 0.4667 |
| 0.4394 | 18.0 | 108 | 2.1433 | 0.4 |
| 0.2725 | 19.0 | 114 | 1.4220 | 0.5556 |
| 0.1718 | 20.0 | 120 | 1.7558 | 0.4667 |
| 0.1718 | 21.0 | 126 | 2.3734 | 0.4667 |
| 0.0642 | 22.0 | 132 | 2.9683 | 0.4667 |
| 0.0642 | 23.0 | 138 | 2.9217 | 0.4889 |
| 0.0435 | 24.0 | 144 | 3.4732 | 0.4667 |
| 0.0409 | 25.0 | 150 | 3.8797 | 0.4667 |
| 0.0409 | 26.0 | 156 | 4.3387 | 0.4444 |
| 0.0418 | 27.0 | 162 | 3.9839 | 0.4444 |
| 0.0418 | 28.0 | 168 | 4.5122 | 0.4444 |
| 0.0035 | 29.0 | 174 | 4.2517 | 0.4444 |
| 0.0006 | 30.0 | 180 | 3.9958 | 0.4444 |
| 0.0006 | 31.0 | 186 | 3.9647 | 0.4444 |
| 0.0004 | 32.0 | 192 | 3.9928 | 0.4444 |
| 0.0004 | 33.0 | 198 | 4.0376 | 0.4222 |
| 0.0003 | 34.0 | 204 | 4.0736 | 0.4222 |
| 0.0002 | 35.0 | 210 | 4.1046 | 0.4222 |
| 0.0002 | 36.0 | 216 | 4.1284 | 0.4222 |
| 0.0002 | 37.0 | 222 | 4.1466 | 0.4222 |
| 0.0002 | 38.0 | 228 | 4.1585 | 0.4222 |
| 0.0002 | 39.0 | 234 | 4.1664 | 0.4222 |
| 0.0002 | 40.0 | 240 | 4.1704 | 0.4222 |
| 0.0002 | 41.0 | 246 | 4.1721 | 0.4222 |
| 0.0002 | 42.0 | 252 | 4.1726 | 0.4222 |
| 0.0002 | 43.0 | 258 | 4.1726 | 0.4222 |
| 0.0002 | 44.0 | 264 | 4.1726 | 0.4222 |
| 0.0002 | 45.0 | 270 | 4.1726 | 0.4222 |
| 0.0002 | 46.0 | 276 | 4.1726 | 0.4222 |
| 0.0002 | 47.0 | 282 | 4.1726 | 0.4222 |
| 0.0002 | 48.0 | 288 | 4.1726 | 0.4222 |
| 0.0002 | 49.0 | 294 | 4.1726 | 0.4222 |
| 0.0002 | 50.0 | 300 | 4.1726 | 0.4222 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1