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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: 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: 0.53125 |
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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: 1.3583 |
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- Accuracy: 0.5312 |
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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 | 1.3917 | 0.5 | |
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| No log | 2.0 | 80 | 1.3327 | 0.525 | |
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| No log | 3.0 | 120 | 1.2901 | 0.5062 | |
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| No log | 4.0 | 160 | 1.3720 | 0.45 | |
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| No log | 5.0 | 200 | 1.4239 | 0.4688 | |
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| No log | 6.0 | 240 | 1.3587 | 0.5125 | |
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| No log | 7.0 | 280 | 1.3874 | 0.5 | |
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| No log | 8.0 | 320 | 1.3341 | 0.5312 | |
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| No log | 9.0 | 360 | 1.2295 | 0.6 | |
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| No log | 10.0 | 400 | 1.3267 | 0.5563 | |
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| No log | 11.0 | 440 | 1.3808 | 0.5375 | |
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| No log | 12.0 | 480 | 1.3547 | 0.55 | |
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| 0.6621 | 13.0 | 520 | 1.5197 | 0.5125 | |
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| 0.6621 | 14.0 | 560 | 1.5709 | 0.525 | |
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| 0.6621 | 15.0 | 600 | 1.4058 | 0.5875 | |
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| 0.6621 | 16.0 | 640 | 1.4561 | 0.5375 | |
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| 0.6621 | 17.0 | 680 | 1.6183 | 0.525 | |
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| 0.6621 | 18.0 | 720 | 1.6036 | 0.525 | |
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| 0.6621 | 19.0 | 760 | 1.5561 | 0.5375 | |
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| 0.6621 | 20.0 | 800 | 1.6527 | 0.5 | |
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| 0.6621 | 21.0 | 840 | 1.7574 | 0.5188 | |
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| 0.6621 | 22.0 | 880 | 1.8418 | 0.475 | |
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| 0.6621 | 23.0 | 920 | 1.5058 | 0.5625 | |
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| 0.6621 | 24.0 | 960 | 1.8427 | 0.4938 | |
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| 0.2166 | 25.0 | 1000 | 1.7561 | 0.4938 | |
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| 0.2166 | 26.0 | 1040 | 1.7327 | 0.525 | |
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| 0.2166 | 27.0 | 1080 | 1.8137 | 0.5125 | |
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| 0.2166 | 28.0 | 1120 | 1.8352 | 0.4938 | |
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| 0.2166 | 29.0 | 1160 | 1.7171 | 0.55 | |
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| 0.2166 | 30.0 | 1200 | 2.0487 | 0.4688 | |
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| 0.2166 | 31.0 | 1240 | 1.8911 | 0.4688 | |
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| 0.2166 | 32.0 | 1280 | 1.5932 | 0.5563 | |
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| 0.2166 | 33.0 | 1320 | 1.7250 | 0.5062 | |
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| 0.2166 | 34.0 | 1360 | 1.9414 | 0.5125 | |
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| 0.2166 | 35.0 | 1400 | 1.9959 | 0.4688 | |
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| 0.2166 | 36.0 | 1440 | 1.9066 | 0.4938 | |
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| 0.2166 | 37.0 | 1480 | 1.8892 | 0.5312 | |
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| 0.1291 | 38.0 | 1520 | 1.8439 | 0.5375 | |
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| 0.1291 | 39.0 | 1560 | 2.0001 | 0.525 | |
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| 0.1291 | 40.0 | 1600 | 1.9060 | 0.5 | |
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| 0.1291 | 41.0 | 1640 | 1.9419 | 0.5375 | |
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| 0.1291 | 42.0 | 1680 | 1.7496 | 0.5563 | |
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| 0.1291 | 43.0 | 1720 | 1.9750 | 0.5188 | |
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| 0.1291 | 44.0 | 1760 | 2.0106 | 0.5188 | |
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| 0.1291 | 45.0 | 1800 | 1.9180 | 0.55 | |
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| 0.1291 | 46.0 | 1840 | 1.9644 | 0.525 | |
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| 0.1291 | 47.0 | 1880 | 1.8182 | 0.5687 | |
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| 0.1291 | 48.0 | 1920 | 1.9591 | 0.5312 | |
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| 0.1291 | 49.0 | 1960 | 1.8103 | 0.5687 | |
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| 0.0866 | 50.0 | 2000 | 2.0038 | 0.5125 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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