metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_tiny_adamax_001_fold2
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_5x_deit_tiny_adamax_001_fold2
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: 5.5945
- 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 |
|---|---|---|---|---|
| 1.3843 | 1.0 | 27 | 1.6047 | 0.2667 |
| 1.3126 | 2.0 | 54 | 1.5540 | 0.2889 |
| 1.242 | 3.0 | 81 | 1.7659 | 0.2889 |
| 1.2292 | 4.0 | 108 | 1.5553 | 0.2667 |
| 1.1861 | 5.0 | 135 | 1.3959 | 0.2889 |
| 0.9837 | 6.0 | 162 | 1.3509 | 0.4889 |
| 0.9151 | 7.0 | 189 | 1.3189 | 0.3778 |
| 0.8428 | 8.0 | 216 | 1.2233 | 0.4444 |
| 0.6366 | 9.0 | 243 | 1.6296 | 0.5556 |
| 0.6056 | 10.0 | 270 | 2.1707 | 0.5333 |
| 0.6193 | 11.0 | 297 | 2.2637 | 0.5333 |
| 0.419 | 12.0 | 324 | 2.6815 | 0.4444 |
| 0.4931 | 13.0 | 351 | 1.6615 | 0.4444 |
| 0.4945 | 14.0 | 378 | 2.3385 | 0.4444 |
| 0.4035 | 15.0 | 405 | 2.2795 | 0.4889 |
| 0.2803 | 16.0 | 432 | 2.9683 | 0.5556 |
| 0.3104 | 17.0 | 459 | 3.6455 | 0.4222 |
| 0.2085 | 18.0 | 486 | 3.8509 | 0.5778 |
| 0.3092 | 19.0 | 513 | 2.7832 | 0.5333 |
| 0.2911 | 20.0 | 540 | 3.5970 | 0.4667 |
| 0.1508 | 21.0 | 567 | 2.8494 | 0.4 |
| 0.1872 | 22.0 | 594 | 3.4606 | 0.5111 |
| 0.1634 | 23.0 | 621 | 3.9940 | 0.5778 |
| 0.0282 | 24.0 | 648 | 4.2310 | 0.4667 |
| 0.0886 | 25.0 | 675 | 3.4801 | 0.4889 |
| 0.1057 | 26.0 | 702 | 3.6632 | 0.4222 |
| 0.0893 | 27.0 | 729 | 3.7806 | 0.5556 |
| 0.0108 | 28.0 | 756 | 4.5566 | 0.5556 |
| 0.1095 | 29.0 | 783 | 4.2488 | 0.5556 |
| 0.0164 | 30.0 | 810 | 4.4510 | 0.5556 |
| 0.0017 | 31.0 | 837 | 4.8182 | 0.5333 |
| 0.0006 | 32.0 | 864 | 5.4595 | 0.5333 |
| 0.0034 | 33.0 | 891 | 5.3273 | 0.5556 |
| 0.0036 | 34.0 | 918 | 4.8258 | 0.4889 |
| 0.0002 | 35.0 | 945 | 5.5297 | 0.5111 |
| 0.0007 | 36.0 | 972 | 5.4553 | 0.4667 |
| 0.0081 | 37.0 | 999 | 5.5834 | 0.5333 |
| 0.0001 | 38.0 | 1026 | 5.4059 | 0.5333 |
| 0.0001 | 39.0 | 1053 | 5.7543 | 0.4667 |
| 0.0 | 40.0 | 1080 | 5.5912 | 0.4667 |
| 0.0 | 41.0 | 1107 | 5.5774 | 0.4667 |
| 0.0 | 42.0 | 1134 | 5.5838 | 0.4667 |
| 0.0 | 43.0 | 1161 | 5.5882 | 0.4667 |
| 0.0 | 44.0 | 1188 | 5.5908 | 0.4667 |
| 0.0 | 45.0 | 1215 | 5.5928 | 0.4667 |
| 0.0 | 46.0 | 1242 | 5.5933 | 0.4667 |
| 0.0 | 47.0 | 1269 | 5.5942 | 0.4667 |
| 0.0 | 48.0 | 1296 | 5.5945 | 0.4667 |
| 0.0 | 49.0 | 1323 | 5.5945 | 0.4667 |
| 0.0 | 50.0 | 1350 | 5.5945 | 0.4667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0