metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_small_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: 0.17777777777777778
hushem_1x_deit_small_sgd_00001_fold2
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: 1.5076
- Accuracy: 0.1778
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 | 1.5128 | 0.1778 |
| 1.5351 | 2.0 | 12 | 1.5126 | 0.1778 |
| 1.5351 | 3.0 | 18 | 1.5123 | 0.1778 |
| 1.521 | 4.0 | 24 | 1.5120 | 0.1778 |
| 1.5462 | 5.0 | 30 | 1.5118 | 0.1778 |
| 1.5462 | 6.0 | 36 | 1.5116 | 0.1778 |
| 1.5099 | 7.0 | 42 | 1.5113 | 0.1778 |
| 1.5099 | 8.0 | 48 | 1.5111 | 0.1778 |
| 1.5333 | 9.0 | 54 | 1.5109 | 0.1778 |
| 1.5206 | 10.0 | 60 | 1.5106 | 0.1778 |
| 1.5206 | 11.0 | 66 | 1.5105 | 0.1778 |
| 1.5227 | 12.0 | 72 | 1.5103 | 0.1778 |
| 1.5227 | 13.0 | 78 | 1.5101 | 0.1778 |
| 1.5256 | 14.0 | 84 | 1.5099 | 0.1778 |
| 1.5395 | 15.0 | 90 | 1.5097 | 0.1778 |
| 1.5395 | 16.0 | 96 | 1.5095 | 0.1778 |
| 1.5169 | 17.0 | 102 | 1.5094 | 0.1778 |
| 1.5169 | 18.0 | 108 | 1.5092 | 0.1778 |
| 1.5502 | 19.0 | 114 | 1.5091 | 0.1778 |
| 1.4882 | 20.0 | 120 | 1.5090 | 0.1778 |
| 1.4882 | 21.0 | 126 | 1.5088 | 0.1778 |
| 1.5202 | 22.0 | 132 | 1.5087 | 0.1778 |
| 1.5202 | 23.0 | 138 | 1.5086 | 0.1778 |
| 1.5139 | 24.0 | 144 | 1.5085 | 0.1778 |
| 1.4995 | 25.0 | 150 | 1.5084 | 0.1778 |
| 1.4995 | 26.0 | 156 | 1.5083 | 0.1778 |
| 1.5175 | 27.0 | 162 | 1.5082 | 0.1778 |
| 1.5175 | 28.0 | 168 | 1.5081 | 0.1778 |
| 1.5365 | 29.0 | 174 | 1.5081 | 0.1778 |
| 1.5232 | 30.0 | 180 | 1.5080 | 0.1778 |
| 1.5232 | 31.0 | 186 | 1.5079 | 0.1778 |
| 1.5236 | 32.0 | 192 | 1.5079 | 0.1778 |
| 1.5236 | 33.0 | 198 | 1.5078 | 0.1778 |
| 1.5292 | 34.0 | 204 | 1.5078 | 0.1778 |
| 1.544 | 35.0 | 210 | 1.5077 | 0.1778 |
| 1.544 | 36.0 | 216 | 1.5077 | 0.1778 |
| 1.4971 | 37.0 | 222 | 1.5077 | 0.1778 |
| 1.4971 | 38.0 | 228 | 1.5077 | 0.1778 |
| 1.4951 | 39.0 | 234 | 1.5076 | 0.1778 |
| 1.5452 | 40.0 | 240 | 1.5076 | 0.1778 |
| 1.5452 | 41.0 | 246 | 1.5076 | 0.1778 |
| 1.5473 | 42.0 | 252 | 1.5076 | 0.1778 |
| 1.5473 | 43.0 | 258 | 1.5076 | 0.1778 |
| 1.5095 | 44.0 | 264 | 1.5076 | 0.1778 |
| 1.495 | 45.0 | 270 | 1.5076 | 0.1778 |
| 1.495 | 46.0 | 276 | 1.5076 | 0.1778 |
| 1.5118 | 47.0 | 282 | 1.5076 | 0.1778 |
| 1.5118 | 48.0 | 288 | 1.5076 | 0.1778 |
| 1.493 | 49.0 | 294 | 1.5076 | 0.1778 |
| 1.528 | 50.0 | 300 | 1.5076 | 0.1778 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1