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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- image-classification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-beans |
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results: [] |
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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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# vit-base-beans |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the ahishamm/HAM_db_enhanced_balanced_reduced_50_20_20_50 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5305 |
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- Accuracy: 0.8451 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 1.0791 | 0.2304 | 100 | 1.0348 | 0.6335 | |
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| 0.9415 | 0.4608 | 200 | 0.9576 | 0.6449 | |
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| 0.7839 | 0.6912 | 300 | 0.8963 | 0.6662 | |
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| 0.7181 | 0.9217 | 400 | 0.8479 | 0.6963 | |
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| 0.3995 | 1.1521 | 500 | 0.7821 | 0.7170 | |
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| 0.5025 | 1.3825 | 600 | 0.6300 | 0.7837 | |
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| 0.4985 | 1.6129 | 700 | 0.7059 | 0.7490 | |
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| 0.4388 | 1.8433 | 800 | 0.5893 | 0.7857 | |
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| 0.2389 | 2.0737 | 900 | 0.5929 | 0.8077 | |
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| 0.2767 | 2.3041 | 1000 | 0.5795 | 0.8091 | |
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| 0.2387 | 2.5346 | 1100 | 0.6100 | 0.8091 | |
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| 0.1691 | 2.7650 | 1200 | 0.6175 | 0.8071 | |
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| 0.1738 | 2.9954 | 1300 | 0.5877 | 0.8198 | |
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| 0.0397 | 3.2258 | 1400 | 0.5766 | 0.8358 | |
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| 0.03 | 3.4562 | 1500 | 0.5681 | 0.8371 | |
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| 0.092 | 3.6866 | 1600 | 0.5305 | 0.8451 | |
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| 0.0416 | 3.9171 | 1700 | 0.5443 | 0.8471 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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