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smids_1x_deit_small_adamax_00001_fold4

Image Classification
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  1. README.md +125 -0
  2. model.safetensors +1 -1
  3. runs/Dec05_09-59-50_28333939ed84/events.out.tfevents.1701770390.28333939ed84.1904.7 +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-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: smids_1x_deit_small_adamax_00001_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: 0.86
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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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+ # smids_1x_deit_small_adamax_00001_fold4
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+
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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: 0.9148
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+ - Accuracy: 0.86
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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: 1e-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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+ - 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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+
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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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+ | 0.5803 | 1.0 | 75 | 0.4968 | 0.8167 |
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+ | 0.4066 | 2.0 | 150 | 0.3965 | 0.8517 |
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+ | 0.3494 | 3.0 | 225 | 0.3679 | 0.8583 |
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+ | 0.257 | 4.0 | 300 | 0.3627 | 0.8583 |
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+ | 0.1968 | 5.0 | 375 | 0.3612 | 0.8567 |
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+ | 0.1309 | 6.0 | 450 | 0.3609 | 0.865 |
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+ | 0.1744 | 7.0 | 525 | 0.3526 | 0.8667 |
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+ | 0.1066 | 8.0 | 600 | 0.3650 | 0.8733 |
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+ | 0.0701 | 9.0 | 675 | 0.3803 | 0.87 |
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+ | 0.058 | 10.0 | 750 | 0.3887 | 0.8683 |
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+ | 0.0585 | 11.0 | 825 | 0.4227 | 0.8667 |
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+ | 0.0507 | 12.0 | 900 | 0.4565 | 0.8667 |
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+ | 0.0443 | 13.0 | 975 | 0.4751 | 0.8667 |
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+ | 0.023 | 14.0 | 1050 | 0.5029 | 0.875 |
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+ | 0.0067 | 15.0 | 1125 | 0.5522 | 0.8667 |
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+ | 0.0046 | 16.0 | 1200 | 0.5758 | 0.8683 |
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+ | 0.0072 | 17.0 | 1275 | 0.6012 | 0.8667 |
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+ | 0.0186 | 18.0 | 1350 | 0.6185 | 0.8667 |
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+ | 0.0049 | 19.0 | 1425 | 0.6452 | 0.8633 |
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+ | 0.0012 | 20.0 | 1500 | 0.6704 | 0.8633 |
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+ | 0.0009 | 21.0 | 1575 | 0.6922 | 0.8633 |
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+ | 0.0009 | 22.0 | 1650 | 0.7205 | 0.8617 |
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+ | 0.0007 | 23.0 | 1725 | 0.7357 | 0.8617 |
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+ | 0.0194 | 24.0 | 1800 | 0.7622 | 0.86 |
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+ | 0.0038 | 25.0 | 1875 | 0.7720 | 0.8583 |
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+ | 0.0005 | 26.0 | 1950 | 0.7827 | 0.86 |
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+ | 0.0003 | 27.0 | 2025 | 0.7974 | 0.8583 |
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+ | 0.0054 | 28.0 | 2100 | 0.8004 | 0.8583 |
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+ | 0.019 | 29.0 | 2175 | 0.8026 | 0.8633 |
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+ | 0.0003 | 30.0 | 2250 | 0.8285 | 0.86 |
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+ | 0.0002 | 31.0 | 2325 | 0.8245 | 0.8617 |
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+ | 0.0002 | 32.0 | 2400 | 0.8349 | 0.86 |
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+ | 0.0002 | 33.0 | 2475 | 0.8577 | 0.8617 |
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+ | 0.0002 | 34.0 | 2550 | 0.8568 | 0.86 |
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+ | 0.0002 | 35.0 | 2625 | 0.8651 | 0.8583 |
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+ | 0.0002 | 36.0 | 2700 | 0.8693 | 0.86 |
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+ | 0.0161 | 37.0 | 2775 | 0.8692 | 0.8633 |
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+ | 0.0002 | 38.0 | 2850 | 0.8782 | 0.8583 |
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+ | 0.0002 | 39.0 | 2925 | 0.8858 | 0.86 |
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+ | 0.0001 | 40.0 | 3000 | 0.8886 | 0.8583 |
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+ | 0.0154 | 41.0 | 3075 | 0.8970 | 0.86 |
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+ | 0.0001 | 42.0 | 3150 | 0.8973 | 0.86 |
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+ | 0.0001 | 43.0 | 3225 | 0.9034 | 0.86 |
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+ | 0.0001 | 44.0 | 3300 | 0.9094 | 0.8617 |
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+ | 0.0001 | 45.0 | 3375 | 0.9094 | 0.86 |
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+ | 0.0001 | 46.0 | 3450 | 0.9101 | 0.86 |
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+ | 0.0001 | 47.0 | 3525 | 0.9123 | 0.86 |
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+ | 0.0001 | 48.0 | 3600 | 0.9135 | 0.86 |
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+ | 0.0001 | 49.0 | 3675 | 0.9142 | 0.86 |
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+ | 0.0001 | 50.0 | 3750 | 0.9148 | 0.86 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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