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smids_5x_deit_tiny_rms_0001_fold3

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-tiny-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_tiny_rms_0001_fold3
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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: 0.9016666666666666
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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_tiny_rms_0001_fold3
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0235
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+ - Accuracy: 0.9017
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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: 0.0001
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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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+ | 0.3072 | 1.0 | 375 | 0.3497 | 0.8733 |
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+ | 0.1839 | 2.0 | 750 | 0.4255 | 0.87 |
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+ | 0.1528 | 3.0 | 1125 | 0.4557 | 0.8567 |
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+ | 0.1267 | 4.0 | 1500 | 0.3726 | 0.89 |
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+ | 0.1353 | 5.0 | 1875 | 0.4467 | 0.8917 |
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+ | 0.0943 | 6.0 | 2250 | 0.4927 | 0.91 |
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+ | 0.1102 | 7.0 | 2625 | 0.6801 | 0.8833 |
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+ | 0.1057 | 8.0 | 3000 | 0.6555 | 0.88 |
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+ | 0.032 | 9.0 | 3375 | 0.7410 | 0.8783 |
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+ | 0.0843 | 10.0 | 3750 | 0.8478 | 0.8667 |
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+ | 0.0459 | 11.0 | 4125 | 0.6987 | 0.8917 |
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+ | 0.0092 | 12.0 | 4500 | 0.7040 | 0.8917 |
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+ | 0.0349 | 13.0 | 4875 | 0.7908 | 0.885 |
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+ | 0.0111 | 14.0 | 5250 | 0.7260 | 0.8983 |
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+ | 0.0286 | 15.0 | 5625 | 0.7556 | 0.89 |
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+ | 0.0202 | 16.0 | 6000 | 0.7922 | 0.885 |
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+ | 0.0017 | 17.0 | 6375 | 0.7780 | 0.89 |
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+ | 0.0426 | 18.0 | 6750 | 0.7356 | 0.9033 |
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+ | 0.0036 | 19.0 | 7125 | 0.7906 | 0.88 |
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+ | 0.0088 | 20.0 | 7500 | 0.8591 | 0.8883 |
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+ | 0.014 | 21.0 | 7875 | 0.9590 | 0.8867 |
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+ | 0.0 | 22.0 | 8250 | 0.9929 | 0.8783 |
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+ | 0.0363 | 23.0 | 8625 | 0.9559 | 0.89 |
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+ | 0.0156 | 24.0 | 9000 | 0.9344 | 0.88 |
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+ | 0.0345 | 25.0 | 9375 | 0.8898 | 0.8917 |
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+ | 0.0005 | 26.0 | 9750 | 0.9066 | 0.9 |
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+ | 0.0104 | 27.0 | 10125 | 0.9018 | 0.8983 |
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+ | 0.0026 | 28.0 | 10500 | 0.8354 | 0.89 |
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+ | 0.0098 | 29.0 | 10875 | 1.0679 | 0.885 |
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+ | 0.0077 | 30.0 | 11250 | 0.8084 | 0.8933 |
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+ | 0.007 | 31.0 | 11625 | 0.9761 | 0.8833 |
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+ | 0.0079 | 32.0 | 12000 | 0.8798 | 0.8867 |
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+ | 0.0211 | 33.0 | 12375 | 0.9152 | 0.8967 |
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+ | 0.0205 | 34.0 | 12750 | 0.8595 | 0.8967 |
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+ | 0.0 | 35.0 | 13125 | 0.9123 | 0.8983 |
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+ | 0.0 | 36.0 | 13500 | 1.0918 | 0.8817 |
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+ | 0.0001 | 37.0 | 13875 | 0.9598 | 0.8917 |
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+ | 0.0 | 38.0 | 14250 | 0.9005 | 0.8933 |
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+ | 0.0 | 39.0 | 14625 | 0.9817 | 0.895 |
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+ | 0.003 | 40.0 | 15000 | 1.0214 | 0.8933 |
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+ | 0.0 | 41.0 | 15375 | 1.0132 | 0.895 |
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+ | 0.0012 | 42.0 | 15750 | 1.0443 | 0.8933 |
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+ | 0.0 | 43.0 | 16125 | 1.0086 | 0.895 |
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+ | 0.0 | 44.0 | 16500 | 1.0148 | 0.895 |
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+ | 0.0 | 45.0 | 16875 | 1.0171 | 0.895 |
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+ | 0.0 | 46.0 | 17250 | 1.0091 | 0.8967 |
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+ | 0.0 | 47.0 | 17625 | 1.0118 | 0.8983 |
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+ | 0.0 | 48.0 | 18000 | 1.0184 | 0.9017 |
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+ | 0.0 | 49.0 | 18375 | 1.0213 | 0.9017 |
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+ | 0.0 | 50.0 | 18750 | 1.0235 | 0.9017 |
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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 2.1.1+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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