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hushem_1x_deit_base_sgd_0001_fold1
hkivancoral/hushem_1x_deit_base_sgd_0001_fold1
hushem_1x_deit_base_sgd_0001_fold1 is a image classification model from hkivancoral. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Nov 15, 2023
- Updated
- Nov 15, 2023
- SHA
- ee204567
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
hushem_1x_deit_base_sgd_0001_fold1
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.5214
- Accuracy: 0.1333
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 | 1.5231 | 0.1333 |
| 1.415 | 2.0 | 12 | 1.5230 | 0.1333 |
| 1.415 | 3.0 | 18 | 1.5229 | 0.1333 |
| 1.4163 | 4.0 | 24 | 1.5228 | 0.1333 |
| 1.412 | 5.0 | 30 | 1.5228 | 0.1333 |
| 1.412 | 6.0 | 36 | 1.5227 | 0.1333 |
| 1.4139 | 7.0 | 42 | 1.5226 | 0.1333 |
| 1.4139 | 8.0 | 48 | 1.5225 | 0.1333 |
| 1.425 | 9.0 | 54 | 1.5225 | 0.1333 |
| 1.4037 | 10.0 | 60 | 1.5224 | 0.1333 |
| 1.4037 | 11.0 | 66 | 1.5223 | 0.1333 |
| 1.4157 | 12.0 | 72 | 1.5223 | 0.1333 |
| 1.4157 | 13.0 | 78 | 1.5222 | 0.1333 |
| 1.4043 | 14.0 | 84 | 1.5221 | 0.1333 |
| 1.4083 | 15.0 | 90 | 1.5221 | 0.1333 |
| 1.4083 | 16.0 | 96 | 1.5220 | 0.1333 |
| 1.4137 | 17.0 | 102 | 1.5220 | 0.1333 |
| 1.4137 | 18.0 | 108 | 1.5219 | 0.1333 |
| 1.4171 | 19.0 | 114 | 1.5219 | 0.1333 |
| 1.4171 | 20.0 | 120 | 1.5218 | 0.1333 |
| 1.4171 | 21.0 | 126 | 1.5218 | 0.1333 |
| 1.415 | 22.0 | 132 | 1.5218 | 0.1333 |
| 1.415 | 23.0 | 138 | 1.5217 | 0.1333 |
| 1.4319 | 24.0 | 144 | 1.5217 | 0.1333 |
| 1.416 | 25.0 | 150 | 1.5217 | 0.1333 |
| 1.416 | 26.0 | 156 | 1.5216 | 0.1333 |
| 1.4082 | 27.0 | 162 | 1.5216 | 0.1333 |
| 1.4082 | 28.0 | 168 | 1.5216 | 0.1333 |
| 1.413 | 29.0 | 174 | 1.5216 | 0.1333 |
| 1.4097 | 30.0 | 180 | 1.5215 | 0.1333 |
| 1.4097 | 31.0 | 186 | 1.5215 | 0.1333 |
| 1.4098 | 32.0 | 192 | 1.5215 | 0.1333 |
| 1.4098 | 33.0 | 198 | 1.5215 | 0.1333 |
| 1.4176 | 34.0 | 204 | 1.5215 | 0.1333 |
| 1.4032 | 35.0 | 210 | 1.5214 | 0.1333 |
| 1.4032 | 36.0 | 216 | 1.5214 | 0.1333 |
| 1.4087 | 37.0 | 222 | 1.5214 | 0.1333 |
| 1.4087 | 38.0 | 228 | 1.5214 | 0.1333 |
| 1.4343 | 39.0 | 234 | 1.5214 | 0.1333 |
| 1.4129 | 40.0 | 240 | 1.5214 | 0.1333 |
| 1.4129 | 41.0 | 246 | 1.5214 | 0.1333 |
| 1.4161 | 42.0 | 252 | 1.5214 | 0.1333 |
| 1.4161 | 43.0 | 258 | 1.5214 | 0.1333 |
| 1.3976 | 44.0 | 264 | 1.5214 | 0.1333 |
| 1.4177 | 45.0 | 270 | 1.5214 | 0.1333 |
| 1.4177 | 46.0 | 276 | 1.5214 | 0.1333 |
| 1.4164 | 47.0 | 282 | 1.5214 | 0.1333 |
| 1.4164 | 48.0 | 288 | 1.5214 | 0.1333 |
| 1.4144 | 49.0 | 294 | 1.5214 | 0.1333 |
| 1.4018 | 50.0 | 300 | 1.5214 | 0.1333 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 15, 2023
- Updated
- Nov 15, 2023