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hkivancoral
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smids_3x_deit_base_rms_00001_fold1

Image Classification
Transformers
PyTorch
vit
generated_from_trainer
Eval Results
Inference Endpoints
Model card Files Community
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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-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: smids_3x_deit_base_rms_00001_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: 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: 0.9115191986644408
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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_3x_deit_base_rms_00001_fold1
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+
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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: 0.7561
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+ - Accuracy: 0.9115
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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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+ | 0.3187 | 1.0 | 226 | 0.2723 | 0.8898 |
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+ | 0.146 | 2.0 | 452 | 0.2372 | 0.9115 |
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+ | 0.0656 | 3.0 | 678 | 0.3870 | 0.8798 |
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+ | 0.0534 | 4.0 | 904 | 0.4524 | 0.8881 |
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+ | 0.0105 | 5.0 | 1130 | 0.4069 | 0.8982 |
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+ | 0.0185 | 6.0 | 1356 | 0.4543 | 0.9032 |
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+ | 0.0005 | 7.0 | 1582 | 0.5107 | 0.8982 |
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+ | 0.004 | 8.0 | 1808 | 0.5982 | 0.8915 |
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+ | 0.0085 | 9.0 | 2034 | 0.5226 | 0.9032 |
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+ | 0.0004 | 10.0 | 2260 | 0.5577 | 0.8998 |
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+ | 0.0002 | 11.0 | 2486 | 0.6123 | 0.8965 |
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+ | 0.0001 | 12.0 | 2712 | 0.5861 | 0.9032 |
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+ | 0.0037 | 13.0 | 2938 | 0.8045 | 0.8865 |
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+ | 0.0067 | 14.0 | 3164 | 0.5419 | 0.9048 |
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+ | 0.0003 | 15.0 | 3390 | 0.5952 | 0.9132 |
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+ | 0.0 | 16.0 | 3616 | 0.5589 | 0.9048 |
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+ | 0.003 | 17.0 | 3842 | 0.5765 | 0.9032 |
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+ | 0.001 | 18.0 | 4068 | 0.6268 | 0.9032 |
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+ | 0.0041 | 19.0 | 4294 | 0.6263 | 0.9098 |
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+ | 0.0 | 20.0 | 4520 | 0.6013 | 0.9065 |
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+ | 0.0134 | 21.0 | 4746 | 0.6132 | 0.9115 |
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+ | 0.0041 | 22.0 | 4972 | 0.5973 | 0.9182 |
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+ | 0.0031 | 23.0 | 5198 | 0.6373 | 0.9082 |
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+ | 0.001 | 24.0 | 5424 | 0.6622 | 0.9149 |
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+ | 0.0 | 25.0 | 5650 | 0.7262 | 0.8965 |
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+ | 0.0 | 26.0 | 5876 | 0.7187 | 0.9082 |
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+ | 0.0 | 27.0 | 6102 | 0.7175 | 0.9082 |
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+ | 0.0 | 28.0 | 6328 | 0.6740 | 0.9082 |
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+ | 0.0 | 29.0 | 6554 | 0.7038 | 0.9082 |
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+ | 0.0 | 30.0 | 6780 | 0.7480 | 0.9015 |
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+ | 0.0 | 31.0 | 7006 | 0.7529 | 0.8998 |
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+ | 0.0 | 32.0 | 7232 | 0.7622 | 0.9048 |
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+ | 0.0029 | 33.0 | 7458 | 0.7367 | 0.9048 |
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+ | 0.0 | 34.0 | 7684 | 0.7218 | 0.9032 |
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+ | 0.0 | 35.0 | 7910 | 0.7442 | 0.8982 |
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+ | 0.0 | 36.0 | 8136 | 0.7444 | 0.9082 |
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+ | 0.0 | 37.0 | 8362 | 0.7439 | 0.9082 |
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+ | 0.0 | 38.0 | 8588 | 0.7353 | 0.9115 |
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+ | 0.0 | 39.0 | 8814 | 0.7431 | 0.9048 |
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+ | 0.0 | 40.0 | 9040 | 0.7357 | 0.9165 |
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+ | 0.0027 | 41.0 | 9266 | 0.7445 | 0.9082 |
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+ | 0.0025 | 42.0 | 9492 | 0.7447 | 0.9098 |
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+ | 0.0 | 43.0 | 9718 | 0.7447 | 0.9065 |
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+ | 0.0 | 44.0 | 9944 | 0.7513 | 0.9098 |
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+ | 0.0 | 45.0 | 10170 | 0.7507 | 0.9132 |
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+ | 0.0 | 46.0 | 10396 | 0.7520 | 0.9132 |
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+ | 0.0 | 47.0 | 10622 | 0.7546 | 0.9115 |
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+ | 0.0 | 48.0 | 10848 | 0.7555 | 0.9115 |
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+ | 0.0 | 49.0 | 11074 | 0.7559 | 0.9115 |
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+ | 0.0 | 50.0 | 11300 | 0.7561 | 0.9115 |
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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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