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BilalMuftuoglu
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deit-base-distilled-patch16-224-75-fold1

Image Classification
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deit
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  2. model.safetensors +1 -1
  3. runs/May22_00-23-31_804716d6a90a/events.out.tfevents.1716337412.804716d6a90a.958.20 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-base-distilled-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: deit-base-distilled-patch16-224-75-fold1
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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: train
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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: 0.8837209302325582
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+ ---
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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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+
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+ # deit-base-distilled-patch16-224-75-fold1
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+
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+ This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3604
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+ - Accuracy: 0.8837
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 2 | 0.6477 | 0.6512 |
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+ | No log | 2.0 | 4 | 0.6528 | 0.6977 |
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+ | No log | 3.0 | 6 | 0.8096 | 0.6977 |
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+ | No log | 4.0 | 8 | 0.7679 | 0.6977 |
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+ | 0.5994 | 5.0 | 10 | 0.5482 | 0.6977 |
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+ | 0.5994 | 6.0 | 12 | 0.4984 | 0.7442 |
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+ | 0.5994 | 7.0 | 14 | 0.6156 | 0.6977 |
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+ | 0.5994 | 8.0 | 16 | 0.5307 | 0.7674 |
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+ | 0.5994 | 9.0 | 18 | 0.4036 | 0.7674 |
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+ | 0.3806 | 10.0 | 20 | 0.4241 | 0.7907 |
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+ | 0.3806 | 11.0 | 22 | 0.4263 | 0.8140 |
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+ | 0.3806 | 12.0 | 24 | 0.6778 | 0.7442 |
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+ | 0.3806 | 13.0 | 26 | 0.5885 | 0.7674 |
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+ | 0.3806 | 14.0 | 28 | 0.6048 | 0.7907 |
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+ | 0.273 | 15.0 | 30 | 0.5110 | 0.8140 |
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+ | 0.273 | 16.0 | 32 | 0.3793 | 0.7442 |
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+ | 0.273 | 17.0 | 34 | 0.3635 | 0.7907 |
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+ | 0.273 | 18.0 | 36 | 0.3863 | 0.8140 |
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+ | 0.273 | 19.0 | 38 | 0.3788 | 0.8372 |
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+ | 0.2388 | 20.0 | 40 | 0.3390 | 0.8140 |
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+ | 0.2388 | 21.0 | 42 | 0.4593 | 0.7907 |
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+ | 0.2388 | 22.0 | 44 | 0.3441 | 0.8605 |
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+ | 0.2388 | 23.0 | 46 | 0.5483 | 0.7907 |
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+ | 0.2388 | 24.0 | 48 | 0.6399 | 0.7907 |
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+ | 0.189 | 25.0 | 50 | 0.3333 | 0.8605 |
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+ | 0.189 | 26.0 | 52 | 0.3326 | 0.8605 |
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+ | 0.189 | 27.0 | 54 | 0.4150 | 0.7907 |
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+ | 0.189 | 28.0 | 56 | 0.3420 | 0.8837 |
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+ | 0.189 | 29.0 | 58 | 0.3649 | 0.8372 |
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+ | 0.1718 | 30.0 | 60 | 0.3651 | 0.8605 |
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+ | 0.1718 | 31.0 | 62 | 0.4676 | 0.8140 |
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+ | 0.1718 | 32.0 | 64 | 0.3543 | 0.8605 |
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+ | 0.1718 | 33.0 | 66 | 0.3209 | 0.8140 |
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+ | 0.1718 | 34.0 | 68 | 0.3420 | 0.8605 |
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+ | 0.1466 | 35.0 | 70 | 0.3800 | 0.8372 |
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+ | 0.1466 | 36.0 | 72 | 0.6547 | 0.8140 |
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+ | 0.1466 | 37.0 | 74 | 0.9743 | 0.7674 |
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+ | 0.1466 | 38.0 | 76 | 0.6677 | 0.7907 |
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+ | 0.1466 | 39.0 | 78 | 0.5691 | 0.8140 |
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+ | 0.119 | 40.0 | 80 | 0.4796 | 0.8605 |
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+ | 0.119 | 41.0 | 82 | 0.3243 | 0.8837 |
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+ | 0.119 | 42.0 | 84 | 0.2969 | 0.8605 |
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+ | 0.119 | 43.0 | 86 | 0.3637 | 0.8372 |
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+ | 0.119 | 44.0 | 88 | 0.3098 | 0.9070 |
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+ | 0.1123 | 45.0 | 90 | 0.3954 | 0.8837 |
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+ | 0.1123 | 46.0 | 92 | 0.3197 | 0.9070 |
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+ | 0.1123 | 47.0 | 94 | 0.3188 | 0.8372 |
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+ | 0.1123 | 48.0 | 96 | 0.3100 | 0.8372 |
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+ | 0.1123 | 49.0 | 98 | 0.3653 | 0.8605 |
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+ | 0.1136 | 50.0 | 100 | 0.3527 | 0.8837 |
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+ | 0.1136 | 51.0 | 102 | 0.3152 | 0.8605 |
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+ | 0.1136 | 52.0 | 104 | 0.3277 | 0.8605 |
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+ | 0.1136 | 53.0 | 106 | 0.3221 | 0.8837 |
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+ | 0.1136 | 54.0 | 108 | 0.3438 | 0.8605 |
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+ | 0.0858 | 55.0 | 110 | 0.4683 | 0.8605 |
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+ | 0.0858 | 56.0 | 112 | 0.4511 | 0.8605 |
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+ | 0.0858 | 57.0 | 114 | 0.3486 | 0.8605 |
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+ | 0.0858 | 58.0 | 116 | 0.3594 | 0.8837 |
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+ | 0.0858 | 59.0 | 118 | 0.3914 | 0.8605 |
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+ | 0.084 | 60.0 | 120 | 0.4257 | 0.8837 |
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+ | 0.084 | 61.0 | 122 | 0.4505 | 0.8837 |
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+ | 0.084 | 62.0 | 124 | 0.4038 | 0.8605 |
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+ | 0.084 | 63.0 | 126 | 0.3745 | 0.8372 |
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+ | 0.084 | 64.0 | 128 | 0.3774 | 0.8140 |
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+ | 0.0938 | 65.0 | 130 | 0.3712 | 0.8140 |
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+ | 0.0938 | 66.0 | 132 | 0.3736 | 0.8140 |
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+ | 0.0938 | 67.0 | 134 | 0.3840 | 0.8605 |
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+ | 0.0938 | 68.0 | 136 | 0.3902 | 0.8605 |
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+ | 0.0938 | 69.0 | 138 | 0.4105 | 0.8605 |
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+ | 0.055 | 70.0 | 140 | 0.4498 | 0.8605 |
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+ | 0.055 | 71.0 | 142 | 0.4954 | 0.8605 |
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+ | 0.055 | 72.0 | 144 | 0.6397 | 0.8605 |
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+ | 0.055 | 73.0 | 146 | 0.6271 | 0.8605 |
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+ | 0.055 | 74.0 | 148 | 0.4821 | 0.8605 |
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+ | 0.0755 | 75.0 | 150 | 0.3699 | 0.9070 |
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+ | 0.0755 | 76.0 | 152 | 0.3303 | 0.8605 |
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+ | 0.0755 | 77.0 | 154 | 0.3282 | 0.8837 |
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+ | 0.0755 | 78.0 | 156 | 0.3181 | 0.8837 |
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+ | 0.0755 | 79.0 | 158 | 0.3083 | 0.8605 |
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+ | 0.0603 | 80.0 | 160 | 0.3170 | 0.8372 |
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+ | 0.0603 | 81.0 | 162 | 0.3397 | 0.8372 |
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+ | 0.0603 | 82.0 | 164 | 0.3538 | 0.8372 |
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+ | 0.0603 | 83.0 | 166 | 0.3461 | 0.8372 |
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+ | 0.0603 | 84.0 | 168 | 0.3337 | 0.8140 |
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+ | 0.0653 | 85.0 | 170 | 0.3330 | 0.8372 |
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+ | 0.0653 | 86.0 | 172 | 0.3451 | 0.8837 |
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+ | 0.0653 | 87.0 | 174 | 0.3612 | 0.8837 |
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+ | 0.0653 | 88.0 | 176 | 0.3822 | 0.8605 |
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+ | 0.0653 | 89.0 | 178 | 0.3875 | 0.8605 |
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+ | 0.0571 | 90.0 | 180 | 0.3845 | 0.8605 |
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+ | 0.0571 | 91.0 | 182 | 0.3642 | 0.8837 |
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+ | 0.0571 | 92.0 | 184 | 0.3529 | 0.8837 |
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+ | 0.0571 | 93.0 | 186 | 0.3471 | 0.8837 |
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+ | 0.0571 | 94.0 | 188 | 0.3540 | 0.8837 |
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+ | 0.069 | 95.0 | 190 | 0.3609 | 0.8837 |
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+ | 0.069 | 96.0 | 192 | 0.3609 | 0.8837 |
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+ | 0.069 | 97.0 | 194 | 0.3634 | 0.8837 |
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+ | 0.069 | 98.0 | 196 | 0.3627 | 0.8837 |
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+ | 0.069 | 99.0 | 198 | 0.3609 | 0.8837 |
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+ | 0.0667 | 100.0 | 200 | 0.3604 | 0.8837 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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