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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: 0.6 |
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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: 1.3404 |
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- Accuracy: 0.6 |
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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: 8 |
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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: 20 |
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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 | 80 | 1.7388 | 0.4188 | |
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| No log | 2.0 | 160 | 1.5325 | 0.4313 | |
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| No log | 3.0 | 240 | 1.3682 | 0.4938 | |
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| No log | 4.0 | 320 | 1.3711 | 0.4813 | |
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| No log | 5.0 | 400 | 1.4485 | 0.425 | |
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| No log | 6.0 | 480 | 1.2649 | 0.5 | |
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| 1.2824 | 7.0 | 560 | 1.3907 | 0.4813 | |
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| 1.2824 | 8.0 | 640 | 1.4983 | 0.4437 | |
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| 1.2824 | 9.0 | 720 | 1.2882 | 0.5625 | |
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| 1.2824 | 10.0 | 800 | 1.3375 | 0.5375 | |
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| 1.2824 | 11.0 | 880 | 1.2640 | 0.5437 | |
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| 1.2824 | 12.0 | 960 | 1.3920 | 0.5188 | |
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| 0.5037 | 13.0 | 1040 | 1.3629 | 0.575 | |
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| 0.5037 | 14.0 | 1120 | 1.4067 | 0.5625 | |
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| 0.5037 | 15.0 | 1200 | 1.3189 | 0.5813 | |
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| 0.5037 | 16.0 | 1280 | 1.3454 | 0.575 | |
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| 0.5037 | 17.0 | 1360 | 1.5200 | 0.5312 | |
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| 0.5037 | 18.0 | 1440 | 1.3378 | 0.6062 | |
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| 0.2616 | 19.0 | 1520 | 1.4539 | 0.5563 | |
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| 0.2616 | 20.0 | 1600 | 1.4415 | 0.5437 | |
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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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