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smids_5x_deit_base_adamax_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_5x_deit_base_adamax_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_5x_deit_base_adamax_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: 0.5548
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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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+ | 0.2913 | 1.0 | 376 | 0.3175 | 0.8815 |
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+ | 0.197 | 2.0 | 752 | 0.2822 | 0.8865 |
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+ | 0.1857 | 3.0 | 1128 | 0.2733 | 0.8915 |
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+ | 0.0801 | 4.0 | 1504 | 0.2769 | 0.8965 |
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+ | 0.062 | 5.0 | 1880 | 0.2932 | 0.9048 |
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+ | 0.0559 | 6.0 | 2256 | 0.3199 | 0.9115 |
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+ | 0.0331 | 7.0 | 2632 | 0.3568 | 0.9098 |
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+ | 0.0024 | 8.0 | 3008 | 0.4098 | 0.8982 |
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+ | 0.0164 | 9.0 | 3384 | 0.4359 | 0.9065 |
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+ | 0.0004 | 10.0 | 3760 | 0.4455 | 0.9082 |
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+ | 0.0127 | 11.0 | 4136 | 0.4881 | 0.9082 |
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+ | 0.0001 | 12.0 | 4512 | 0.4919 | 0.9032 |
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+ | 0.0001 | 13.0 | 4888 | 0.4968 | 0.9115 |
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+ | 0.0037 | 14.0 | 5264 | 0.5278 | 0.9065 |
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+ | 0.0001 | 15.0 | 5640 | 0.5316 | 0.9115 |
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+ | 0.0001 | 16.0 | 6016 | 0.5363 | 0.9032 |
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+ | 0.0001 | 17.0 | 6392 | 0.5212 | 0.9149 |
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+ | 0.0001 | 18.0 | 6768 | 0.5353 | 0.9098 |
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+ | 0.0 | 19.0 | 7144 | 0.5265 | 0.9098 |
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+ | 0.0147 | 20.0 | 7520 | 0.5277 | 0.9115 |
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+ | 0.0 | 21.0 | 7896 | 0.5565 | 0.9065 |
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+ | 0.0 | 22.0 | 8272 | 0.5728 | 0.9098 |
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+ | 0.0 | 23.0 | 8648 | 0.5461 | 0.9115 |
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+ | 0.0 | 24.0 | 9024 | 0.5300 | 0.9065 |
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+ | 0.0 | 25.0 | 9400 | 0.5373 | 0.9065 |
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+ | 0.0042 | 26.0 | 9776 | 0.5315 | 0.9082 |
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+ | 0.0 | 27.0 | 10152 | 0.5779 | 0.9065 |
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+ | 0.0 | 28.0 | 10528 | 0.5457 | 0.9098 |
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+ | 0.0079 | 29.0 | 10904 | 0.5511 | 0.9098 |
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+ | 0.003 | 30.0 | 11280 | 0.5454 | 0.9048 |
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+ | 0.0 | 31.0 | 11656 | 0.5479 | 0.9098 |
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+ | 0.0 | 32.0 | 12032 | 0.5371 | 0.9082 |
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+ | 0.0 | 33.0 | 12408 | 0.5701 | 0.9065 |
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+ | 0.0 | 34.0 | 12784 | 0.5431 | 0.9032 |
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+ | 0.0 | 35.0 | 13160 | 0.5470 | 0.9048 |
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+ | 0.0 | 36.0 | 13536 | 0.5461 | 0.9015 |
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+ | 0.0 | 37.0 | 13912 | 0.5481 | 0.9115 |
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+ | 0.0 | 38.0 | 14288 | 0.5522 | 0.9098 |
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+ | 0.0 | 39.0 | 14664 | 0.5539 | 0.9082 |
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+ | 0.0 | 40.0 | 15040 | 0.5537 | 0.9115 |
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+ | 0.0 | 41.0 | 15416 | 0.5471 | 0.9048 |
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+ | 0.0 | 42.0 | 15792 | 0.5483 | 0.9115 |
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+ | 0.0 | 43.0 | 16168 | 0.5497 | 0.9132 |
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+ | 0.0 | 44.0 | 16544 | 0.5527 | 0.9115 |
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+ | 0.0 | 45.0 | 16920 | 0.5532 | 0.9115 |
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+ | 0.0053 | 46.0 | 17296 | 0.5512 | 0.9098 |
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+ | 0.0 | 47.0 | 17672 | 0.5538 | 0.9115 |
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+ | 0.0 | 48.0 | 18048 | 0.5539 | 0.9098 |
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+ | 0.0 | 49.0 | 18424 | 0.5540 | 0.9115 |
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+ | 0.0012 | 50.0 | 18800 | 0.5548 | 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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