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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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- 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: Rashed-vit-model |
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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: train |
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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: 1.0 |
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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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# Rashed-vit-model |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0047 |
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- Accuracy: 1.0 |
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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: 4 |
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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: 50 |
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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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| 0.2279 | 1.9048 | 200 | 0.4485 | 0.9111 | |
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| 0.1335 | 3.8095 | 400 | 0.0680 | 0.9889 | |
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| 0.0061 | 5.7143 | 600 | 0.0047 | 1.0 | |
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| 0.0025 | 7.6190 | 800 | 0.0606 | 0.9778 | |
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| 0.0624 | 9.5238 | 1000 | 0.2500 | 0.9556 | |
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| 0.0013 | 11.4286 | 1200 | 0.0868 | 0.9889 | |
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| 0.001 | 13.3333 | 1400 | 0.0908 | 0.9889 | |
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| 0.0008 | 15.2381 | 1600 | 0.0935 | 0.9889 | |
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| 0.0006 | 17.1429 | 1800 | 0.0960 | 0.9889 | |
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| 0.0005 | 19.0476 | 2000 | 0.0979 | 0.9889 | |
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| 0.0004 | 20.9524 | 2200 | 0.0996 | 0.9889 | |
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| 0.0004 | 22.8571 | 2400 | 0.1013 | 0.9889 | |
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| 0.0003 | 24.7619 | 2600 | 0.1027 | 0.9889 | |
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| 0.0003 | 26.6667 | 2800 | 0.1040 | 0.9889 | |
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| 0.0003 | 28.5714 | 3000 | 0.1054 | 0.9889 | |
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| 0.0002 | 30.4762 | 3200 | 0.1065 | 0.9889 | |
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| 0.0002 | 32.3810 | 3400 | 0.1076 | 0.9889 | |
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| 0.0002 | 34.2857 | 3600 | 0.1085 | 0.9889 | |
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| 0.0002 | 36.1905 | 3800 | 0.1094 | 0.9889 | |
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| 0.0002 | 38.0952 | 4000 | 0.1102 | 0.9889 | |
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| 0.0002 | 40.0 | 4200 | 0.1109 | 0.9889 | |
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| 0.0001 | 41.9048 | 4400 | 0.1115 | 0.9889 | |
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| 0.0001 | 43.8095 | 4600 | 0.1120 | 0.9889 | |
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| 0.0001 | 45.7143 | 4800 | 0.1124 | 0.9889 | |
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| 0.0001 | 47.6190 | 5000 | 0.1126 | 0.9889 | |
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| 0.0001 | 49.5238 | 5200 | 0.1128 | 0.9889 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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