metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_tiny_sgd_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: 0.6888888888888889
hushem_40x_deit_tiny_sgd_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: 1.0440
- Accuracy: 0.6889
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 |
---|---|---|---|---|
1.0975 | 1.0 | 215 | 1.3370 | 0.3778 |
0.8761 | 2.0 | 430 | 1.2895 | 0.4444 |
0.7359 | 3.0 | 645 | 1.2565 | 0.4889 |
0.6277 | 4.0 | 860 | 1.2398 | 0.5556 |
0.5094 | 5.0 | 1075 | 1.2052 | 0.5556 |
0.4187 | 6.0 | 1290 | 1.1950 | 0.5778 |
0.3909 | 7.0 | 1505 | 1.1310 | 0.6 |
0.3137 | 8.0 | 1720 | 1.1412 | 0.5556 |
0.2817 | 9.0 | 1935 | 1.0706 | 0.5778 |
0.2108 | 10.0 | 2150 | 1.0537 | 0.6 |
0.1785 | 11.0 | 2365 | 1.0606 | 0.5778 |
0.1677 | 12.0 | 2580 | 1.0202 | 0.5778 |
0.1602 | 13.0 | 2795 | 1.0251 | 0.5778 |
0.1355 | 14.0 | 3010 | 1.0164 | 0.6 |
0.1234 | 15.0 | 3225 | 1.0019 | 0.5778 |
0.0937 | 16.0 | 3440 | 0.9960 | 0.6 |
0.0963 | 17.0 | 3655 | 0.9708 | 0.5778 |
0.0998 | 18.0 | 3870 | 0.9907 | 0.5778 |
0.0604 | 19.0 | 4085 | 0.9932 | 0.6 |
0.0724 | 20.0 | 4300 | 0.9792 | 0.5556 |
0.0616 | 21.0 | 4515 | 0.9528 | 0.5556 |
0.0591 | 22.0 | 4730 | 0.9741 | 0.5556 |
0.0433 | 23.0 | 4945 | 0.9824 | 0.5556 |
0.0476 | 24.0 | 5160 | 0.9907 | 0.5556 |
0.0326 | 25.0 | 5375 | 0.9714 | 0.5778 |
0.0325 | 26.0 | 5590 | 0.9834 | 0.6 |
0.0352 | 27.0 | 5805 | 0.9903 | 0.5778 |
0.0319 | 28.0 | 6020 | 0.9831 | 0.5778 |
0.0242 | 29.0 | 6235 | 0.9872 | 0.6 |
0.0238 | 30.0 | 6450 | 1.0027 | 0.6222 |
0.0166 | 31.0 | 6665 | 0.9985 | 0.5778 |
0.0151 | 32.0 | 6880 | 1.0088 | 0.6 |
0.0176 | 33.0 | 7095 | 1.0180 | 0.6 |
0.0221 | 34.0 | 7310 | 1.0038 | 0.6444 |
0.0159 | 35.0 | 7525 | 0.9868 | 0.6667 |
0.0115 | 36.0 | 7740 | 1.0104 | 0.6444 |
0.017 | 37.0 | 7955 | 1.0128 | 0.6889 |
0.0105 | 38.0 | 8170 | 1.0250 | 0.6444 |
0.0144 | 39.0 | 8385 | 1.0115 | 0.6889 |
0.0092 | 40.0 | 8600 | 1.0202 | 0.6667 |
0.0131 | 41.0 | 8815 | 1.0296 | 0.6444 |
0.0108 | 42.0 | 9030 | 1.0274 | 0.6889 |
0.0089 | 43.0 | 9245 | 1.0423 | 0.6889 |
0.0153 | 44.0 | 9460 | 1.0420 | 0.6889 |
0.0077 | 45.0 | 9675 | 1.0387 | 0.6667 |
0.0096 | 46.0 | 9890 | 1.0413 | 0.6889 |
0.0073 | 47.0 | 10105 | 1.0431 | 0.6889 |
0.0112 | 48.0 | 10320 | 1.0453 | 0.6889 |
0.0085 | 49.0 | 10535 | 1.0438 | 0.6889 |
0.01 | 50.0 | 10750 | 1.0440 | 0.6889 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2