metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_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: 0.2222222222222222
hushem_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: 1.7073
- Accuracy: 0.2222
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.7237 | 0.2222 |
| 1.719 | 2.0 | 12 | 1.7228 | 0.2222 |
| 1.719 | 3.0 | 18 | 1.7220 | 0.2222 |
| 1.7128 | 4.0 | 24 | 1.7212 | 0.2222 |
| 1.7405 | 5.0 | 30 | 1.7204 | 0.2222 |
| 1.7405 | 6.0 | 36 | 1.7197 | 0.2222 |
| 1.6943 | 7.0 | 42 | 1.7190 | 0.2222 |
| 1.6943 | 8.0 | 48 | 1.7183 | 0.2222 |
| 1.6759 | 9.0 | 54 | 1.7176 | 0.2222 |
| 1.7158 | 10.0 | 60 | 1.7169 | 0.2222 |
| 1.7158 | 11.0 | 66 | 1.7162 | 0.2222 |
| 1.7024 | 12.0 | 72 | 1.7156 | 0.2222 |
| 1.7024 | 13.0 | 78 | 1.7150 | 0.2222 |
| 1.7744 | 14.0 | 84 | 1.7144 | 0.2222 |
| 1.7251 | 15.0 | 90 | 1.7139 | 0.2222 |
| 1.7251 | 16.0 | 96 | 1.7134 | 0.2222 |
| 1.6942 | 17.0 | 102 | 1.7129 | 0.2222 |
| 1.6942 | 18.0 | 108 | 1.7124 | 0.2222 |
| 1.7154 | 19.0 | 114 | 1.7120 | 0.2222 |
| 1.6829 | 20.0 | 120 | 1.7115 | 0.2222 |
| 1.6829 | 21.0 | 126 | 1.7111 | 0.2222 |
| 1.6559 | 22.0 | 132 | 1.7107 | 0.2222 |
| 1.6559 | 23.0 | 138 | 1.7104 | 0.2222 |
| 1.7194 | 24.0 | 144 | 1.7100 | 0.2222 |
| 1.6925 | 25.0 | 150 | 1.7097 | 0.2222 |
| 1.6925 | 26.0 | 156 | 1.7094 | 0.2222 |
| 1.6919 | 27.0 | 162 | 1.7091 | 0.2222 |
| 1.6919 | 28.0 | 168 | 1.7089 | 0.2222 |
| 1.6948 | 29.0 | 174 | 1.7086 | 0.2222 |
| 1.7059 | 30.0 | 180 | 1.7084 | 0.2222 |
| 1.7059 | 31.0 | 186 | 1.7082 | 0.2222 |
| 1.7337 | 32.0 | 192 | 1.7080 | 0.2222 |
| 1.7337 | 33.0 | 198 | 1.7079 | 0.2222 |
| 1.6587 | 34.0 | 204 | 1.7077 | 0.2222 |
| 1.7172 | 35.0 | 210 | 1.7076 | 0.2222 |
| 1.7172 | 36.0 | 216 | 1.7075 | 0.2222 |
| 1.7051 | 37.0 | 222 | 1.7075 | 0.2222 |
| 1.7051 | 38.0 | 228 | 1.7074 | 0.2222 |
| 1.6141 | 39.0 | 234 | 1.7074 | 0.2222 |
| 1.6784 | 40.0 | 240 | 1.7073 | 0.2222 |
| 1.6784 | 41.0 | 246 | 1.7073 | 0.2222 |
| 1.6991 | 42.0 | 252 | 1.7073 | 0.2222 |
| 1.6991 | 43.0 | 258 | 1.7073 | 0.2222 |
| 1.7247 | 44.0 | 264 | 1.7073 | 0.2222 |
| 1.6773 | 45.0 | 270 | 1.7073 | 0.2222 |
| 1.6773 | 46.0 | 276 | 1.7073 | 0.2222 |
| 1.6939 | 47.0 | 282 | 1.7073 | 0.2222 |
| 1.6939 | 48.0 | 288 | 1.7073 | 0.2222 |
| 1.6622 | 49.0 | 294 | 1.7073 | 0.2222 |
| 1.7192 | 50.0 | 300 | 1.7073 | 0.2222 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1