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smids_5x_deit_base_adamax_0001_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_0001_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: 0.9181969949916527
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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_0001_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: 0.6997
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+ - Accuracy: 0.9182
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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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+ | 0.2162 | 1.0 | 376 | 0.2261 | 0.9082 |
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+ | 0.1041 | 2.0 | 752 | 0.2663 | 0.8965 |
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+ | 0.0837 | 3.0 | 1128 | 0.3441 | 0.9015 |
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+ | 0.0172 | 4.0 | 1504 | 0.4099 | 0.9048 |
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+ | 0.0131 | 5.0 | 1880 | 0.4724 | 0.9048 |
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+ | 0.0004 | 6.0 | 2256 | 0.4925 | 0.9065 |
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+ | 0.0017 | 7.0 | 2632 | 0.6831 | 0.8965 |
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+ | 0.0006 | 8.0 | 3008 | 0.5273 | 0.9015 |
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+ | 0.0324 | 9.0 | 3384 | 0.5755 | 0.8998 |
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+ | 0.0 | 10.0 | 3760 | 0.6569 | 0.9048 |
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+ | 0.0009 | 11.0 | 4136 | 0.5873 | 0.9082 |
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+ | 0.0003 | 12.0 | 4512 | 0.6069 | 0.9065 |
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+ | 0.0 | 13.0 | 4888 | 0.5862 | 0.9082 |
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+ | 0.0063 | 14.0 | 5264 | 0.6445 | 0.9048 |
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+ | 0.0 | 15.0 | 5640 | 0.6277 | 0.9132 |
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+ | 0.0 | 16.0 | 6016 | 0.7053 | 0.9032 |
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+ | 0.0 | 17.0 | 6392 | 0.6033 | 0.9098 |
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+ | 0.0 | 18.0 | 6768 | 0.6638 | 0.9065 |
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+ | 0.0 | 19.0 | 7144 | 0.6432 | 0.9082 |
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+ | 0.004 | 20.0 | 7520 | 0.6467 | 0.9115 |
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+ | 0.0 | 21.0 | 7896 | 0.7009 | 0.9115 |
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+ | 0.0 | 22.0 | 8272 | 0.7221 | 0.9048 |
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+ | 0.0 | 23.0 | 8648 | 0.6516 | 0.9149 |
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+ | 0.0 | 24.0 | 9024 | 0.6399 | 0.9149 |
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+ | 0.0 | 25.0 | 9400 | 0.6382 | 0.9182 |
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+ | 0.0034 | 26.0 | 9776 | 0.6520 | 0.9098 |
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+ | 0.0 | 27.0 | 10152 | 0.6761 | 0.9115 |
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+ | 0.0 | 28.0 | 10528 | 0.6436 | 0.9182 |
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+ | 0.003 | 29.0 | 10904 | 0.6339 | 0.9115 |
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+ | 0.0041 | 30.0 | 11280 | 0.6392 | 0.9132 |
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+ | 0.0 | 31.0 | 11656 | 0.6548 | 0.9182 |
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+ | 0.0 | 32.0 | 12032 | 0.6680 | 0.9149 |
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+ | 0.0 | 33.0 | 12408 | 0.6562 | 0.9115 |
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+ | 0.0 | 34.0 | 12784 | 0.6705 | 0.9165 |
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+ | 0.0 | 35.0 | 13160 | 0.6801 | 0.9098 |
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+ | 0.0 | 36.0 | 13536 | 0.6653 | 0.9182 |
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+ | 0.0 | 37.0 | 13912 | 0.6565 | 0.9165 |
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+ | 0.0 | 38.0 | 14288 | 0.6618 | 0.9215 |
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+ | 0.0 | 39.0 | 14664 | 0.6597 | 0.9149 |
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+ | 0.0 | 40.0 | 15040 | 0.6689 | 0.9165 |
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+ | 0.0 | 41.0 | 15416 | 0.6826 | 0.9149 |
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+ | 0.0 | 42.0 | 15792 | 0.6835 | 0.9132 |
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+ | 0.0 | 43.0 | 16168 | 0.6862 | 0.9149 |
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+ | 0.0 | 44.0 | 16544 | 0.6860 | 0.9182 |
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+ | 0.0 | 45.0 | 16920 | 0.6904 | 0.9182 |
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+ | 0.0027 | 46.0 | 17296 | 0.6967 | 0.9132 |
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+ | 0.0 | 47.0 | 17672 | 0.6971 | 0.9182 |
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+ | 0.0 | 48.0 | 18048 | 0.6989 | 0.9182 |
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+ | 0.0 | 49.0 | 18424 | 0.7000 | 0.9182 |
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+ | 0.0022 | 50.0 | 18800 | 0.6997 | 0.9182 |
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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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