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smids_10x_deit_small_rms_001_fold5

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-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_rms_001_fold5
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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: 0.7166666666666667
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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_rms_001_fold5
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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: 0.6302
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+ - Accuracy: 0.7167
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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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+ | 1.1023 | 1.0 | 750 | 1.0958 | 0.34 |
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+ | 0.9402 | 2.0 | 1500 | 0.9088 | 0.5033 |
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+ | 0.9044 | 3.0 | 2250 | 0.8761 | 0.5383 |
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+ | 0.8247 | 4.0 | 3000 | 0.8349 | 0.5233 |
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+ | 0.7854 | 5.0 | 3750 | 0.8127 | 0.5633 |
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+ | 0.7771 | 6.0 | 4500 | 0.8860 | 0.5383 |
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+ | 0.773 | 7.0 | 5250 | 0.8230 | 0.575 |
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+ | 0.8024 | 8.0 | 6000 | 0.7956 | 0.5883 |
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+ | 0.8797 | 9.0 | 6750 | 0.8015 | 0.6183 |
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+ | 0.7815 | 10.0 | 7500 | 0.7866 | 0.6083 |
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+ | 0.7914 | 11.0 | 8250 | 0.7547 | 0.6267 |
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+ | 0.7411 | 12.0 | 9000 | 0.7615 | 0.59 |
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+ | 0.7343 | 13.0 | 9750 | 0.7214 | 0.6617 |
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+ | 0.7764 | 14.0 | 10500 | 0.7295 | 0.6717 |
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+ | 0.7555 | 15.0 | 11250 | 0.7012 | 0.6617 |
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+ | 0.7373 | 16.0 | 12000 | 0.7948 | 0.6217 |
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+ | 0.6985 | 17.0 | 12750 | 0.7396 | 0.6267 |
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+ | 0.7821 | 18.0 | 13500 | 0.7384 | 0.66 |
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+ | 0.7914 | 19.0 | 14250 | 0.7821 | 0.635 |
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+ | 0.7863 | 20.0 | 15000 | 0.7254 | 0.655 |
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+ | 0.6932 | 21.0 | 15750 | 0.7242 | 0.6633 |
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+ | 0.6744 | 22.0 | 16500 | 0.7009 | 0.6817 |
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+ | 0.6983 | 23.0 | 17250 | 0.6866 | 0.7133 |
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+ | 0.6779 | 24.0 | 18000 | 0.6963 | 0.6983 |
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+ | 0.6937 | 25.0 | 18750 | 0.6942 | 0.6817 |
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+ | 0.6943 | 26.0 | 19500 | 0.6864 | 0.695 |
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+ | 0.6231 | 27.0 | 20250 | 0.7126 | 0.665 |
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+ | 0.6418 | 28.0 | 21000 | 0.6620 | 0.6983 |
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+ | 0.72 | 29.0 | 21750 | 0.6656 | 0.7017 |
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+ | 0.7042 | 30.0 | 22500 | 0.6697 | 0.6867 |
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+ | 0.754 | 31.0 | 23250 | 0.6511 | 0.7033 |
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+ | 0.6987 | 32.0 | 24000 | 0.6765 | 0.69 |
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+ | 0.7166 | 33.0 | 24750 | 0.6802 | 0.7083 |
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+ | 0.6725 | 34.0 | 25500 | 0.6763 | 0.7033 |
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+ | 0.6612 | 35.0 | 26250 | 0.6382 | 0.7083 |
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+ | 0.6967 | 36.0 | 27000 | 0.6445 | 0.705 |
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+ | 0.6491 | 37.0 | 27750 | 0.6443 | 0.7133 |
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+ | 0.7274 | 38.0 | 28500 | 0.6314 | 0.7333 |
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+ | 0.6904 | 39.0 | 29250 | 0.6429 | 0.7267 |
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+ | 0.6516 | 40.0 | 30000 | 0.6385 | 0.7167 |
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+ | 0.6647 | 41.0 | 30750 | 0.6386 | 0.7 |
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+ | 0.666 | 42.0 | 31500 | 0.6656 | 0.695 |
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+ | 0.6901 | 43.0 | 32250 | 0.6568 | 0.715 |
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+ | 0.6021 | 44.0 | 33000 | 0.6375 | 0.7117 |
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+ | 0.6467 | 45.0 | 33750 | 0.6267 | 0.7117 |
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+ | 0.6249 | 46.0 | 34500 | 0.6374 | 0.71 |
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+ | 0.6161 | 47.0 | 35250 | 0.6354 | 0.71 |
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+ | 0.6534 | 48.0 | 36000 | 0.6396 | 0.715 |
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+ | 0.6031 | 49.0 | 36750 | 0.6326 | 0.7117 |
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+ | 0.6145 | 50.0 | 37500 | 0.6302 | 0.7167 |
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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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