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_sgd_001_fold1
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_5x_deit_tiny_sgd_001_fold1
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: 1.3348
- 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 |
|---|---|---|---|---|
| 1.4407 | 1.0 | 27 | 1.4410 | 0.2667 |
| 1.382 | 2.0 | 54 | 1.4092 | 0.2667 |
| 1.3657 | 3.0 | 81 | 1.3896 | 0.2889 |
| 1.3344 | 4.0 | 108 | 1.3798 | 0.3111 |
| 1.2537 | 5.0 | 135 | 1.3657 | 0.3111 |
| 1.2237 | 6.0 | 162 | 1.3512 | 0.3333 |
| 1.2007 | 7.0 | 189 | 1.3419 | 0.3333 |
| 1.1972 | 8.0 | 216 | 1.3343 | 0.3556 |
| 1.1733 | 9.0 | 243 | 1.3294 | 0.3556 |
| 1.1145 | 10.0 | 270 | 1.3216 | 0.3778 |
| 1.1155 | 11.0 | 297 | 1.3166 | 0.3778 |
| 1.036 | 12.0 | 324 | 1.3103 | 0.3778 |
| 1.0595 | 13.0 | 351 | 1.3110 | 0.3778 |
| 1.0374 | 14.0 | 378 | 1.3072 | 0.3556 |
| 1.0659 | 15.0 | 405 | 1.3094 | 0.3778 |
| 1.034 | 16.0 | 432 | 1.3075 | 0.3778 |
| 0.954 | 17.0 | 459 | 1.3079 | 0.3778 |
| 0.9531 | 18.0 | 486 | 1.3085 | 0.3778 |
| 0.957 | 19.0 | 513 | 1.3124 | 0.3778 |
| 0.8978 | 20.0 | 540 | 1.3062 | 0.3778 |
| 0.885 | 21.0 | 567 | 1.3090 | 0.3778 |
| 0.8819 | 22.0 | 594 | 1.3143 | 0.3778 |
| 0.8801 | 23.0 | 621 | 1.3162 | 0.3778 |
| 0.857 | 24.0 | 648 | 1.3096 | 0.3778 |
| 0.8479 | 25.0 | 675 | 1.3101 | 0.3778 |
| 0.8743 | 26.0 | 702 | 1.3127 | 0.4 |
| 0.8288 | 27.0 | 729 | 1.3204 | 0.4 |
| 0.8104 | 28.0 | 756 | 1.3212 | 0.4 |
| 0.8245 | 29.0 | 783 | 1.3255 | 0.4 |
| 0.8139 | 30.0 | 810 | 1.3165 | 0.4 |
| 0.796 | 31.0 | 837 | 1.3232 | 0.4 |
| 0.7919 | 32.0 | 864 | 1.3216 | 0.4 |
| 0.7796 | 33.0 | 891 | 1.3211 | 0.4 |
| 0.7571 | 34.0 | 918 | 1.3245 | 0.4222 |
| 0.7521 | 35.0 | 945 | 1.3258 | 0.4222 |
| 0.7479 | 36.0 | 972 | 1.3280 | 0.4222 |
| 0.7621 | 37.0 | 999 | 1.3305 | 0.4222 |
| 0.7058 | 38.0 | 1026 | 1.3305 | 0.4222 |
| 0.71 | 39.0 | 1053 | 1.3319 | 0.4222 |
| 0.7228 | 40.0 | 1080 | 1.3314 | 0.4222 |
| 0.7146 | 41.0 | 1107 | 1.3317 | 0.4222 |
| 0.7189 | 42.0 | 1134 | 1.3333 | 0.4222 |
| 0.7405 | 43.0 | 1161 | 1.3338 | 0.4222 |
| 0.6872 | 44.0 | 1188 | 1.3335 | 0.4222 |
| 0.6996 | 45.0 | 1215 | 1.3344 | 0.4222 |
| 0.6979 | 46.0 | 1242 | 1.3345 | 0.4222 |
| 0.7035 | 47.0 | 1269 | 1.3347 | 0.4222 |
| 0.703 | 48.0 | 1296 | 1.3347 | 0.4222 |
| 0.7245 | 49.0 | 1323 | 1.3348 | 0.4222 |
| 0.7019 | 50.0 | 1350 | 1.3348 | 0.4222 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0