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-small-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_small_sgd_0001_fold5
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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: 0.2682926829268293
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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_small_sgd_0001_fold5
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This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4475
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- Accuracy: 0.2683
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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: 0.0001
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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 | 1.5161 | 0.2439 |
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| 1.5359 | 2.0 | 12 | 1.5118 | 0.2439 |
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| 1.5359 | 3.0 | 18 | 1.5076 | 0.2439 |
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| 1.5171 | 4.0 | 24 | 1.5040 | 0.2439 |
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| 1.5208 | 5.0 | 30 | 1.5002 | 0.2683 |
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| 1.5208 | 6.0 | 36 | 1.4969 | 0.2683 |
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| 1.5066 | 7.0 | 42 | 1.4937 | 0.2683 |
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| 1.5066 | 8.0 | 48 | 1.4908 | 0.2683 |
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| 1.4941 | 9.0 | 54 | 1.4878 | 0.2683 |
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| 1.4953 | 10.0 | 60 | 1.4851 | 0.2683 |
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| 1.4953 | 11.0 | 66 | 1.4825 | 0.2683 |
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| 1.498 | 12.0 | 72 | 1.4798 | 0.2683 |
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| 1.498 | 13.0 | 78 | 1.4774 | 0.2683 |
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| 1.465 | 14.0 | 84 | 1.4753 | 0.2683 |
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| 1.4811 | 15.0 | 90 | 1.4730 | 0.2683 |
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| 1.4811 | 16.0 | 96 | 1.4709 | 0.2683 |
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| 1.476 | 17.0 | 102 | 1.4689 | 0.2683 |
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| 1.476 | 18.0 | 108 | 1.4672 | 0.2683 |
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| 1.4977 | 19.0 | 114 | 1.4656 | 0.2683 |
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| 1.4745 | 20.0 | 120 | 1.4639 | 0.2683 |
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| 1.4745 | 21.0 | 126 | 1.4624 | 0.2683 |
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| 1.4662 | 22.0 | 132 | 1.4609 | 0.2683 |
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| 1.4662 | 23.0 | 138 | 1.4594 | 0.2683 |
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| 1.4905 | 24.0 | 144 | 1.4581 | 0.2683 |
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| 1.465 | 25.0 | 150 | 1.4568 | 0.2683 |
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| 1.465 | 26.0 | 156 | 1.4556 | 0.2683 |
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| 1.4499 | 27.0 | 162 | 1.4545 | 0.2683 |
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| 1.4499 | 28.0 | 168 | 1.4535 | 0.2683 |
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| 1.473 | 29.0 | 174 | 1.4527 | 0.2683 |
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| 1.4704 | 30.0 | 180 | 1.4520 | 0.2683 |
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| 1.4704 | 31.0 | 186 | 1.4512 | 0.2683 |
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| 1.4654 | 32.0 | 192 | 1.4506 | 0.2683 |
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| 1.4654 | 33.0 | 198 | 1.4500 | 0.2683 |
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| 1.4322 | 34.0 | 204 | 1.4494 | 0.2683 |
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| 1.459 | 35.0 | 210 | 1.4490 | 0.2683 |
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| 1.459 | 36.0 | 216 | 1.4486 | 0.2683 |
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| 1.4499 | 37.0 | 222 | 1.4482 | 0.2683 |
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| 1.4499 | 38.0 | 228 | 1.4480 | 0.2683 |
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| 1.4314 | 39.0 | 234 | 1.4477 | 0.2683 |
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| 1.4745 | 40.0 | 240 | 1.4476 | 0.2683 |
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| 1.4745 | 41.0 | 246 | 1.4476 | 0.2683 |
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| 1.4482 | 42.0 | 252 | 1.4475 | 0.2683 |
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| 1.4482 | 43.0 | 258 | 1.4475 | 0.2683 |
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| 1.4526 | 44.0 | 264 | 1.4475 | 0.2683 |
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| 1.4693 | 45.0 | 270 | 1.4475 | 0.2683 |
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| 1.4693 | 46.0 | 276 | 1.4475 | 0.2683 |
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| 1.4506 | 47.0 | 282 | 1.4475 | 0.2683 |
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| 1.4506 | 48.0 | 288 | 1.4475 | 0.2683 |
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| 1.4529 | 49.0 | 294 | 1.4475 | 0.2683 |
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| 1.4667 | 50.0 | 300 | 1.4475 | 0.2683 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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model.safetensors
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runs/Nov13_19-01-23_bee0b91e9507/events.out.tfevents.1699902084.bee0b91e9507.899.9
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