metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_deit_tiny_sgd_00001_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: 0.3544093178036606
smids_1x_deit_tiny_sgd_00001_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: 1.1866
- Accuracy: 0.3544
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: 1e-05
- 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 |
|---|---|---|---|---|
| 1.3496 | 1.0 | 75 | 1.3448 | 0.3444 |
| 1.342 | 2.0 | 150 | 1.3359 | 0.3444 |
| 1.3049 | 3.0 | 225 | 1.3273 | 0.3428 |
| 1.3212 | 4.0 | 300 | 1.3189 | 0.3428 |
| 1.2683 | 5.0 | 375 | 1.3112 | 0.3394 |
| 1.3476 | 6.0 | 450 | 1.3037 | 0.3394 |
| 1.3281 | 7.0 | 525 | 1.2966 | 0.3378 |
| 1.2813 | 8.0 | 600 | 1.2897 | 0.3394 |
| 1.3177 | 9.0 | 675 | 1.2831 | 0.3394 |
| 1.2768 | 10.0 | 750 | 1.2769 | 0.3394 |
| 1.2973 | 11.0 | 825 | 1.2710 | 0.3394 |
| 1.2616 | 12.0 | 900 | 1.2654 | 0.3428 |
| 1.2694 | 13.0 | 975 | 1.2600 | 0.3428 |
| 1.1891 | 14.0 | 1050 | 1.2550 | 0.3361 |
| 1.2441 | 15.0 | 1125 | 1.2502 | 0.3411 |
| 1.211 | 16.0 | 1200 | 1.2456 | 0.3428 |
| 1.247 | 17.0 | 1275 | 1.2413 | 0.3411 |
| 1.2791 | 18.0 | 1350 | 1.2372 | 0.3411 |
| 1.2453 | 19.0 | 1425 | 1.2333 | 0.3428 |
| 1.2386 | 20.0 | 1500 | 1.2296 | 0.3444 |
| 1.2461 | 21.0 | 1575 | 1.2262 | 0.3461 |
| 1.2333 | 22.0 | 1650 | 1.2229 | 0.3461 |
| 1.2716 | 23.0 | 1725 | 1.2198 | 0.3478 |
| 1.2019 | 24.0 | 1800 | 1.2169 | 0.3461 |
| 1.1715 | 25.0 | 1875 | 1.2141 | 0.3444 |
| 1.1932 | 26.0 | 1950 | 1.2116 | 0.3461 |
| 1.2512 | 27.0 | 2025 | 1.2092 | 0.3444 |
| 1.1951 | 28.0 | 2100 | 1.2069 | 0.3444 |
| 1.2421 | 29.0 | 2175 | 1.2047 | 0.3461 |
| 1.1922 | 30.0 | 2250 | 1.2027 | 0.3478 |
| 1.2041 | 31.0 | 2325 | 1.2008 | 0.3478 |
| 1.2208 | 32.0 | 2400 | 1.1991 | 0.3478 |
| 1.1905 | 33.0 | 2475 | 1.1975 | 0.3478 |
| 1.1949 | 34.0 | 2550 | 1.1960 | 0.3478 |
| 1.1944 | 35.0 | 2625 | 1.1946 | 0.3527 |
| 1.1832 | 36.0 | 2700 | 1.1934 | 0.3561 |
| 1.2088 | 37.0 | 2775 | 1.1923 | 0.3577 |
| 1.2643 | 38.0 | 2850 | 1.1913 | 0.3594 |
| 1.2153 | 39.0 | 2925 | 1.1904 | 0.3561 |
| 1.2054 | 40.0 | 3000 | 1.1896 | 0.3561 |
| 1.188 | 41.0 | 3075 | 1.1889 | 0.3561 |
| 1.2171 | 42.0 | 3150 | 1.1883 | 0.3577 |
| 1.1949 | 43.0 | 3225 | 1.1878 | 0.3577 |
| 1.159 | 44.0 | 3300 | 1.1874 | 0.3561 |
| 1.1443 | 45.0 | 3375 | 1.1871 | 0.3544 |
| 1.1683 | 46.0 | 3450 | 1.1869 | 0.3544 |
| 1.2029 | 47.0 | 3525 | 1.1867 | 0.3544 |
| 1.1913 | 48.0 | 3600 | 1.1867 | 0.3544 |
| 1.1814 | 49.0 | 3675 | 1.1866 | 0.3544 |
| 1.1739 | 50.0 | 3750 | 1.1866 | 0.3544 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0