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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: image_classification |
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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: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.575 |
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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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# image_classification |
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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: 1.5646 |
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- Accuracy: 0.575 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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| No log | 1.0 | 40 | 1.8666 | 0.3312 | |
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| No log | 2.0 | 80 | 1.5679 | 0.4188 | |
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| No log | 3.0 | 120 | 1.4168 | 0.5062 | |
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| No log | 4.0 | 160 | 1.2966 | 0.5563 | |
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| No log | 5.0 | 200 | 1.3039 | 0.45 | |
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| No log | 6.0 | 240 | 1.2528 | 0.5188 | |
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| No log | 7.0 | 280 | 1.2559 | 0.525 | |
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| No log | 8.0 | 320 | 1.2510 | 0.55 | |
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| No log | 9.0 | 360 | 1.3209 | 0.525 | |
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| No log | 10.0 | 400 | 1.2598 | 0.5188 | |
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| No log | 11.0 | 440 | 1.3478 | 0.5 | |
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| No log | 12.0 | 480 | 1.2411 | 0.5625 | |
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| 1.0456 | 13.0 | 520 | 1.2945 | 0.575 | |
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| 1.0456 | 14.0 | 560 | 1.3332 | 0.5 | |
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| 1.0456 | 15.0 | 600 | 1.2186 | 0.5875 | |
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| 1.0456 | 16.0 | 640 | 1.2907 | 0.5563 | |
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| 1.0456 | 17.0 | 680 | 1.3378 | 0.5312 | |
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| 1.0456 | 18.0 | 720 | 1.4472 | 0.5375 | |
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| 1.0456 | 19.0 | 760 | 1.1642 | 0.6438 | |
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| 1.0456 | 20.0 | 800 | 1.2972 | 0.5437 | |
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| 1.0456 | 21.0 | 840 | 1.3696 | 0.5875 | |
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| 1.0456 | 22.0 | 880 | 1.4568 | 0.5375 | |
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| 1.0456 | 23.0 | 920 | 1.3409 | 0.5625 | |
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| 1.0456 | 24.0 | 960 | 1.3188 | 0.5687 | |
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| 0.2919 | 25.0 | 1000 | 1.4131 | 0.5813 | |
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| 0.2919 | 26.0 | 1040 | 1.3066 | 0.575 | |
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| 0.2919 | 27.0 | 1080 | 1.4908 | 0.5375 | |
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| 0.2919 | 28.0 | 1120 | 1.4409 | 0.5563 | |
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| 0.2919 | 29.0 | 1160 | 1.5531 | 0.5188 | |
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| 0.2919 | 30.0 | 1200 | 1.4412 | 0.5938 | |
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| 0.2919 | 31.0 | 1240 | 1.4300 | 0.575 | |
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| 0.2919 | 32.0 | 1280 | 1.6232 | 0.5375 | |
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| 0.2919 | 33.0 | 1320 | 1.4592 | 0.6 | |
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| 0.2919 | 34.0 | 1360 | 1.3311 | 0.6312 | |
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| 0.2919 | 35.0 | 1400 | 1.5094 | 0.5625 | |
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| 0.2919 | 36.0 | 1440 | 1.3694 | 0.6062 | |
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| 0.2919 | 37.0 | 1480 | 1.5205 | 0.5813 | |
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| 0.1643 | 38.0 | 1520 | 1.4502 | 0.6125 | |
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| 0.1643 | 39.0 | 1560 | 1.2809 | 0.6625 | |
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| 0.1643 | 40.0 | 1600 | 1.6043 | 0.5563 | |
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| 0.1643 | 41.0 | 1640 | 1.5729 | 0.5625 | |
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| 0.1643 | 42.0 | 1680 | 1.5918 | 0.5625 | |
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| 0.1643 | 43.0 | 1720 | 1.5747 | 0.575 | |
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| 0.1643 | 44.0 | 1760 | 1.6325 | 0.5437 | |
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| 0.1643 | 45.0 | 1800 | 1.5850 | 0.575 | |
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| 0.1643 | 46.0 | 1840 | 1.6558 | 0.575 | |
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| 0.1643 | 47.0 | 1880 | 1.4821 | 0.5875 | |
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| 0.1643 | 48.0 | 1920 | 1.6070 | 0.575 | |
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| 0.1643 | 49.0 | 1960 | 1.6660 | 0.525 | |
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| 0.1152 | 50.0 | 2000 | 1.5803 | 0.575 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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