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smids_10x_deit_small_sgd_001_fold2

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
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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_10x_deit_small_sgd_001_fold2
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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: 0.8685524126455907
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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_10x_deit_small_sgd_001_fold2
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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: 0.3138
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+ - Accuracy: 0.8686
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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: 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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+
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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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+ | 0.5167 | 1.0 | 750 | 0.5666 | 0.7737 |
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+ | 0.3469 | 2.0 | 1500 | 0.4420 | 0.8136 |
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+ | 0.3157 | 3.0 | 2250 | 0.3924 | 0.8336 |
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+ | 0.3366 | 4.0 | 3000 | 0.3644 | 0.8469 |
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+ | 0.2937 | 5.0 | 3750 | 0.3504 | 0.8569 |
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+ | 0.2683 | 6.0 | 4500 | 0.3342 | 0.8602 |
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+ | 0.2786 | 7.0 | 5250 | 0.3236 | 0.8636 |
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+ | 0.2458 | 8.0 | 6000 | 0.3168 | 0.8619 |
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+ | 0.2409 | 9.0 | 6750 | 0.3122 | 0.8586 |
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+ | 0.2266 | 10.0 | 7500 | 0.3079 | 0.8652 |
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+ | 0.2724 | 11.0 | 8250 | 0.3033 | 0.8586 |
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+ | 0.2793 | 12.0 | 9000 | 0.3021 | 0.8586 |
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+ | 0.2082 | 13.0 | 9750 | 0.3016 | 0.8619 |
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+ | 0.152 | 14.0 | 10500 | 0.3001 | 0.8669 |
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+ | 0.1732 | 15.0 | 11250 | 0.2977 | 0.8636 |
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+ | 0.1629 | 16.0 | 12000 | 0.2993 | 0.8636 |
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+ | 0.1493 | 17.0 | 12750 | 0.2962 | 0.8669 |
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+ | 0.1762 | 18.0 | 13500 | 0.2975 | 0.8669 |
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+ | 0.1954 | 19.0 | 14250 | 0.2989 | 0.8735 |
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+ | 0.1979 | 20.0 | 15000 | 0.2956 | 0.8636 |
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+ | 0.1452 | 21.0 | 15750 | 0.2997 | 0.8636 |
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+ | 0.1414 | 22.0 | 16500 | 0.2986 | 0.8636 |
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+ | 0.131 | 23.0 | 17250 | 0.2989 | 0.8652 |
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+ | 0.1633 | 24.0 | 18000 | 0.2990 | 0.8652 |
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+ | 0.1429 | 25.0 | 18750 | 0.3003 | 0.8636 |
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+ | 0.2373 | 26.0 | 19500 | 0.3030 | 0.8735 |
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+ | 0.1884 | 27.0 | 20250 | 0.3051 | 0.8702 |
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+ | 0.1254 | 28.0 | 21000 | 0.3031 | 0.8602 |
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+ | 0.1804 | 29.0 | 21750 | 0.3034 | 0.8719 |
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+ | 0.1437 | 30.0 | 22500 | 0.3048 | 0.8686 |
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+ | 0.1608 | 31.0 | 23250 | 0.3012 | 0.8669 |
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+ | 0.1618 | 32.0 | 24000 | 0.3040 | 0.8652 |
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+ | 0.1429 | 33.0 | 24750 | 0.3043 | 0.8602 |
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+ | 0.1612 | 34.0 | 25500 | 0.3075 | 0.8652 |
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+ | 0.1719 | 35.0 | 26250 | 0.3075 | 0.8619 |
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+ | 0.1633 | 36.0 | 27000 | 0.3103 | 0.8669 |
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+ | 0.1619 | 37.0 | 27750 | 0.3071 | 0.8636 |
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+ | 0.1665 | 38.0 | 28500 | 0.3086 | 0.8669 |
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+ | 0.1293 | 39.0 | 29250 | 0.3088 | 0.8669 |
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+ | 0.1641 | 40.0 | 30000 | 0.3125 | 0.8719 |
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+ | 0.1466 | 41.0 | 30750 | 0.3125 | 0.8702 |
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+ | 0.1482 | 42.0 | 31500 | 0.3110 | 0.8652 |
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+ | 0.1022 | 43.0 | 32250 | 0.3124 | 0.8652 |
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+ | 0.1075 | 44.0 | 33000 | 0.3116 | 0.8669 |
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+ | 0.1257 | 45.0 | 33750 | 0.3131 | 0.8669 |
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+ | 0.1217 | 46.0 | 34500 | 0.3119 | 0.8669 |
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+ | 0.1431 | 47.0 | 35250 | 0.3120 | 0.8686 |
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+ | 0.1086 | 48.0 | 36000 | 0.3131 | 0.8686 |
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+ | 0.1041 | 49.0 | 36750 | 0.3136 | 0.8686 |
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+ | 0.1201 | 50.0 | 37500 | 0.3138 | 0.8686 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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