hkivancoral
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End of training
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README.md
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---
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license: apache-2.0
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base_model: facebook/deit-base-patch16-224
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: hushem_1x_deit_base_adamax_001_fold4
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: test
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.5952380952380952
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# hushem_1x_deit_base_adamax_001_fold4
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This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.6471
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- Accuracy: 0.5952
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 50
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 6 | 1.4889 | 0.2381 |
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| 1.6928 | 2.0 | 12 | 1.4102 | 0.2381 |
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| 1.6928 | 3.0 | 18 | 1.2949 | 0.4048 |
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| 1.4466 | 4.0 | 24 | 1.1224 | 0.4762 |
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| 1.3026 | 5.0 | 30 | 1.3079 | 0.3333 |
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| 1.3026 | 6.0 | 36 | 1.0368 | 0.6190 |
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| 1.2798 | 7.0 | 42 | 1.2143 | 0.3571 |
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| 1.2798 | 8.0 | 48 | 1.0732 | 0.5 |
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| 1.1914 | 9.0 | 54 | 1.0366 | 0.5476 |
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| 1.2164 | 10.0 | 60 | 1.0675 | 0.5 |
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| 1.2164 | 11.0 | 66 | 1.0841 | 0.4762 |
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| 1.2177 | 12.0 | 72 | 1.1092 | 0.5952 |
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| 1.2177 | 13.0 | 78 | 0.9871 | 0.5238 |
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| 1.183 | 14.0 | 84 | 1.1380 | 0.4762 |
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| 1.2146 | 15.0 | 90 | 1.1128 | 0.5 |
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| 1.2146 | 16.0 | 96 | 0.9957 | 0.5952 |
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| 1.1103 | 17.0 | 102 | 1.0192 | 0.5952 |
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| 1.1103 | 18.0 | 108 | 1.1751 | 0.5 |
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| 1.0656 | 19.0 | 114 | 1.1301 | 0.5 |
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| 1.047 | 20.0 | 120 | 1.1327 | 0.4048 |
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| 1.047 | 21.0 | 126 | 1.2359 | 0.4762 |
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| 0.8853 | 22.0 | 132 | 1.1524 | 0.5952 |
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| 0.8853 | 23.0 | 138 | 1.9551 | 0.3095 |
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| 0.7611 | 24.0 | 144 | 1.3513 | 0.5 |
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| 0.7727 | 25.0 | 150 | 1.6490 | 0.5476 |
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| 0.7727 | 26.0 | 156 | 1.0702 | 0.4048 |
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| 0.8546 | 27.0 | 162 | 1.7107 | 0.3333 |
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| 0.8546 | 28.0 | 168 | 1.3302 | 0.4286 |
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| 0.695 | 29.0 | 174 | 1.1947 | 0.5714 |
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| 0.4593 | 30.0 | 180 | 1.8330 | 0.4762 |
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| 0.4593 | 31.0 | 186 | 1.6031 | 0.5952 |
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| 0.2978 | 32.0 | 192 | 2.1238 | 0.6190 |
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| 0.2978 | 33.0 | 198 | 2.3897 | 0.5476 |
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| 0.2625 | 34.0 | 204 | 2.1147 | 0.6190 |
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| 0.1062 | 35.0 | 210 | 2.6950 | 0.5 |
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| 0.1062 | 36.0 | 216 | 2.5016 | 0.6190 |
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| 0.0682 | 37.0 | 222 | 2.6327 | 0.5476 |
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| 0.0682 | 38.0 | 228 | 2.5000 | 0.5714 |
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| 0.0309 | 39.0 | 234 | 2.4431 | 0.6190 |
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| 0.019 | 40.0 | 240 | 2.6997 | 0.5714 |
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| 0.019 | 41.0 | 246 | 2.6710 | 0.5952 |
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| 0.0078 | 42.0 | 252 | 2.6471 | 0.5952 |
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| 0.0078 | 43.0 | 258 | 2.6471 | 0.5952 |
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| 0.0071 | 44.0 | 264 | 2.6471 | 0.5952 |
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| 0.0054 | 45.0 | 270 | 2.6471 | 0.5952 |
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| 0.0054 | 46.0 | 276 | 2.6471 | 0.5952 |
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| 0.0076 | 47.0 | 282 | 2.6471 | 0.5952 |
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| 0.0076 | 48.0 | 288 | 2.6471 | 0.5952 |
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| 0.0053 | 49.0 | 294 | 2.6471 | 0.5952 |
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| 0.0059 | 50.0 | 300 | 2.6471 | 0.5952 |
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### Framework versions
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- Transformers 4.35.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.7
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- Tokenizers 0.14.1
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model.safetensors
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runs/Nov15_13-55-37_2fc4888c5945/events.out.tfevents.1700056538.2fc4888c5945.935.3
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