metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_small_sgd_00001_fold3
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: 0.48833333333333334
smids_5x_deit_small_sgd_00001_fold3
This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0078
- Accuracy: 0.4883
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 |
|---|---|---|---|---|
| 1.0625 | 1.0 | 375 | 1.0854 | 0.38 |
| 1.055 | 2.0 | 750 | 1.0820 | 0.3817 |
| 1.0441 | 3.0 | 1125 | 1.0787 | 0.3817 |
| 1.0543 | 4.0 | 1500 | 1.0755 | 0.3833 |
| 1.0717 | 5.0 | 1875 | 1.0724 | 0.3833 |
| 1.0405 | 6.0 | 2250 | 1.0694 | 0.3833 |
| 1.0573 | 7.0 | 2625 | 1.0664 | 0.3867 |
| 1.052 | 8.0 | 3000 | 1.0635 | 0.3933 |
| 1.0402 | 9.0 | 3375 | 1.0606 | 0.395 |
| 1.026 | 10.0 | 3750 | 1.0579 | 0.3967 |
| 1.0363 | 11.0 | 4125 | 1.0552 | 0.4017 |
| 1.044 | 12.0 | 4500 | 1.0526 | 0.4033 |
| 1.0227 | 13.0 | 4875 | 1.0501 | 0.4117 |
| 1.0237 | 14.0 | 5250 | 1.0477 | 0.4133 |
| 1.0137 | 15.0 | 5625 | 1.0453 | 0.4183 |
| 1.005 | 16.0 | 6000 | 1.0431 | 0.4167 |
| 1.0298 | 17.0 | 6375 | 1.0409 | 0.4167 |
| 1.0209 | 18.0 | 6750 | 1.0387 | 0.4183 |
| 1.0296 | 19.0 | 7125 | 1.0366 | 0.425 |
| 1.0081 | 20.0 | 7500 | 1.0346 | 0.4283 |
| 0.9849 | 21.0 | 7875 | 1.0327 | 0.4317 |
| 1.0033 | 22.0 | 8250 | 1.0308 | 0.44 |
| 1.0003 | 23.0 | 8625 | 1.0290 | 0.4417 |
| 1.0236 | 24.0 | 9000 | 1.0274 | 0.445 |
| 0.9768 | 25.0 | 9375 | 1.0257 | 0.4533 |
| 0.9963 | 26.0 | 9750 | 1.0242 | 0.4567 |
| 0.9973 | 27.0 | 10125 | 1.0227 | 0.46 |
| 1.025 | 28.0 | 10500 | 1.0213 | 0.4617 |
| 0.9786 | 29.0 | 10875 | 1.0199 | 0.465 |
| 1.0006 | 30.0 | 11250 | 1.0187 | 0.4667 |
| 1.0183 | 31.0 | 11625 | 1.0175 | 0.47 |
| 0.9871 | 32.0 | 12000 | 1.0164 | 0.4733 |
| 0.9751 | 33.0 | 12375 | 1.0154 | 0.4733 |
| 0.9558 | 34.0 | 12750 | 1.0144 | 0.475 |
| 0.9521 | 35.0 | 13125 | 1.0135 | 0.475 |
| 0.975 | 36.0 | 13500 | 1.0127 | 0.475 |
| 0.9912 | 37.0 | 13875 | 1.0119 | 0.4783 |
| 0.9818 | 38.0 | 14250 | 1.0112 | 0.48 |
| 0.9973 | 39.0 | 14625 | 1.0106 | 0.4817 |
| 0.9737 | 40.0 | 15000 | 1.0101 | 0.4833 |
| 0.9571 | 41.0 | 15375 | 1.0096 | 0.4833 |
| 0.9497 | 42.0 | 15750 | 1.0092 | 0.4833 |
| 0.9898 | 43.0 | 16125 | 1.0088 | 0.485 |
| 0.9733 | 44.0 | 16500 | 1.0085 | 0.485 |
| 0.9695 | 45.0 | 16875 | 1.0083 | 0.4833 |
| 0.9603 | 46.0 | 17250 | 1.0081 | 0.4867 |
| 0.9924 | 47.0 | 17625 | 1.0079 | 0.4867 |
| 0.9781 | 48.0 | 18000 | 1.0079 | 0.4867 |
| 1.0064 | 49.0 | 18375 | 1.0078 | 0.4883 |
| 0.9488 | 50.0 | 18750 | 1.0078 | 0.4883 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2