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hushem_1x_deit_base_rms_001_fold1
hkivancoral/hushem_1x_deit_base_rms_001_fold1
hushem_1x_deit_base_rms_001_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 16, 2023
- Updated
- Nov 16, 2023
- SHA
- 1cabcb82
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_rms_001_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: 2.0515
- Accuracy: 0.4444
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 5.7295 | 0.2444 |
| 3.8216 | 2.0 | 12 | 3.3899 | 0.2444 |
| 3.8216 | 3.0 | 18 | 1.9221 | 0.2444 |
| 2.0397 | 4.0 | 24 | 1.5517 | 0.2667 |
| 1.7061 | 5.0 | 30 | 1.6113 | 0.2444 |
| 1.7061 | 6.0 | 36 | 1.5745 | 0.2667 |
| 1.5185 | 7.0 | 42 | 1.5819 | 0.2444 |
| 1.5185 | 8.0 | 48 | 1.5544 | 0.2667 |
| 1.5399 | 9.0 | 54 | 1.4265 | 0.2667 |
| 1.4704 | 10.0 | 60 | 1.4555 | 0.2444 |
| 1.4704 | 11.0 | 66 | 1.5190 | 0.2667 |
| 1.4477 | 12.0 | 72 | 1.4505 | 0.2444 |
| 1.4477 | 13.0 | 78 | 1.4958 | 0.2667 |
| 1.4478 | 14.0 | 84 | 1.3383 | 0.2667 |
| 1.4577 | 15.0 | 90 | 1.2186 | 0.4444 |
| 1.4577 | 16.0 | 96 | 1.3020 | 0.4 |
| 1.4812 | 17.0 | 102 | 1.3485 | 0.3333 |
| 1.4812 | 18.0 | 108 | 1.2420 | 0.4889 |
| 1.357 | 19.0 | 114 | 1.5123 | 0.2889 |
| 1.2669 | 20.0 | 120 | 1.0806 | 0.5111 |
| 1.2669 | 21.0 | 126 | 1.2866 | 0.3778 |
| 1.1674 | 22.0 | 132 | 1.2669 | 0.4 |
| 1.1674 | 23.0 | 138 | 1.2024 | 0.4222 |
| 1.0892 | 24.0 | 144 | 1.1560 | 0.5111 |
| 1.1158 | 25.0 | 150 | 1.3838 | 0.4 |
| 1.1158 | 26.0 | 156 | 1.3008 | 0.4667 |
| 0.9418 | 27.0 | 162 | 1.2353 | 0.4667 |
| 0.9418 | 28.0 | 168 | 1.1679 | 0.4667 |
| 0.9251 | 29.0 | 174 | 1.5982 | 0.4 |
| 0.8116 | 30.0 | 180 | 1.4467 | 0.4222 |
| 0.8116 | 31.0 | 186 | 1.4759 | 0.4222 |
| 0.7877 | 32.0 | 192 | 1.7036 | 0.4222 |
| 0.7877 | 33.0 | 198 | 1.5198 | 0.4667 |
| 0.8255 | 34.0 | 204 | 1.6264 | 0.4444 |
| 0.6324 | 35.0 | 210 | 1.5460 | 0.4444 |
| 0.6324 | 36.0 | 216 | 1.7519 | 0.4444 |
| 0.6569 | 37.0 | 222 | 2.1790 | 0.4222 |
| 0.6569 | 38.0 | 228 | 2.1337 | 0.4667 |
| 0.4724 | 39.0 | 234 | 1.5947 | 0.4889 |
| 0.4698 | 40.0 | 240 | 2.2448 | 0.4444 |
| 0.4698 | 41.0 | 246 | 2.0575 | 0.4444 |
| 0.3953 | 42.0 | 252 | 2.0515 | 0.4444 |
| 0.3953 | 43.0 | 258 | 2.0515 | 0.4444 |
| 0.4352 | 44.0 | 264 | 2.0515 | 0.4444 |
| 0.3453 | 45.0 | 270 | 2.0515 | 0.4444 |
| 0.3453 | 46.0 | 276 | 2.0515 | 0.4444 |
| 0.3689 | 47.0 | 282 | 2.0515 | 0.4444 |
| 0.3689 | 48.0 | 288 | 2.0515 | 0.4444 |
| 0.3565 | 49.0 | 294 | 2.0515 | 0.4444 |
| 0.3737 | 50.0 | 300 | 2.0515 | 0.4444 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 16, 2023
- Updated
- Nov 16, 2023