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hushem_1x_deit_base_rms_0001_fold1
hkivancoral/hushem_1x_deit_base_rms_0001_fold1
hushem_1x_deit_base_rms_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 16, 2023
- Updated
- Nov 16, 2023
- SHA
- 29b68c2f
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_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: 3.1229
- Accuracy: 0.5778
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: 0.0001
- 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 | 1.8872 | 0.2444 |
| 1.9577 | 2.0 | 12 | 1.4317 | 0.2444 |
| 1.9577 | 3.0 | 18 | 1.4241 | 0.2444 |
| 1.42 | 4.0 | 24 | 1.4307 | 0.2444 |
| 1.3849 | 5.0 | 30 | 1.3737 | 0.4222 |
| 1.3849 | 6.0 | 36 | 1.3932 | 0.3111 |
| 1.4386 | 7.0 | 42 | 1.7764 | 0.2444 |
| 1.4386 | 8.0 | 48 | 1.3602 | 0.2667 |
| 1.258 | 9.0 | 54 | 2.0427 | 0.3778 |
| 1.1111 | 10.0 | 60 | 1.1310 | 0.4889 |
| 1.1111 | 11.0 | 66 | 2.7936 | 0.3778 |
| 0.8089 | 12.0 | 72 | 1.1048 | 0.5333 |
| 0.8089 | 13.0 | 78 | 1.5229 | 0.4 |
| 0.6344 | 14.0 | 84 | 2.4918 | 0.4222 |
| 0.3674 | 15.0 | 90 | 1.2248 | 0.5333 |
| 0.3674 | 16.0 | 96 | 1.9743 | 0.5333 |
| 0.1742 | 17.0 | 102 | 2.3841 | 0.4444 |
| 0.1742 | 18.0 | 108 | 3.0361 | 0.4222 |
| 0.1094 | 19.0 | 114 | 2.4775 | 0.5778 |
| 0.0149 | 20.0 | 120 | 2.7557 | 0.6 |
| 0.0149 | 21.0 | 126 | 2.8306 | 0.6 |
| 0.0005 | 22.0 | 132 | 2.8795 | 0.6 |
| 0.0005 | 23.0 | 138 | 2.9199 | 0.6 |
| 0.0004 | 24.0 | 144 | 2.9515 | 0.6 |
| 0.0003 | 25.0 | 150 | 2.9748 | 0.6 |
| 0.0003 | 26.0 | 156 | 2.9936 | 0.6 |
| 0.0002 | 27.0 | 162 | 3.0112 | 0.6 |
| 0.0002 | 28.0 | 168 | 3.0280 | 0.6 |
| 0.0002 | 29.0 | 174 | 3.0414 | 0.6 |
| 0.0002 | 30.0 | 180 | 3.0544 | 0.6 |
| 0.0002 | 31.0 | 186 | 3.0664 | 0.6 |
| 0.0002 | 32.0 | 192 | 3.0752 | 0.6 |
| 0.0002 | 33.0 | 198 | 3.0851 | 0.5778 |
| 0.0002 | 34.0 | 204 | 3.0929 | 0.5778 |
| 0.0002 | 35.0 | 210 | 3.0988 | 0.5778 |
| 0.0002 | 36.0 | 216 | 3.1066 | 0.5778 |
| 0.0002 | 37.0 | 222 | 3.1117 | 0.5778 |
| 0.0002 | 38.0 | 228 | 3.1165 | 0.5778 |
| 0.0001 | 39.0 | 234 | 3.1194 | 0.5778 |
| 0.0001 | 40.0 | 240 | 3.1215 | 0.5778 |
| 0.0001 | 41.0 | 246 | 3.1226 | 0.5778 |
| 0.0001 | 42.0 | 252 | 3.1229 | 0.5778 |
| 0.0001 | 43.0 | 258 | 3.1229 | 0.5778 |
| 0.0001 | 44.0 | 264 | 3.1229 | 0.5778 |
| 0.0001 | 45.0 | 270 | 3.1229 | 0.5778 |
| 0.0001 | 46.0 | 276 | 3.1229 | 0.5778 |
| 0.0001 | 47.0 | 282 | 3.1229 | 0.5778 |
| 0.0001 | 48.0 | 288 | 3.1229 | 0.5778 |
| 0.0001 | 49.0 | 294 | 3.1229 | 0.5778 |
| 0.0001 | 50.0 | 300 | 3.1229 | 0.5778 |
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