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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: vit-base-patch16-224-in21k-finetuned-gecko |
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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: test |
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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: 0.988479262672811 |
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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-patch16-224-in21k-finetuned-gecko |
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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: 0.1890 |
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- Accuracy: 0.9885 |
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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: 0.0005 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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 | 0.97 | 21 | 3.2699 | 0.6210 | |
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| No log | 1.98 | 43 | 2.0011 | 0.8468 | |
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| 3.1155 | 2.99 | 65 | 1.2851 | 0.8641 | |
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| 3.1155 | 4.0 | 87 | 0.7751 | 0.9389 | |
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| 1.1003 | 4.97 | 108 | 0.6060 | 0.9274 | |
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| 1.1003 | 5.98 | 130 | 0.4584 | 0.9378 | |
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| 0.5229 | 6.99 | 152 | 0.3417 | 0.9585 | |
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| 0.5229 | 8.0 | 174 | 0.2415 | 0.9816 | |
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| 0.5229 | 8.97 | 195 | 0.2014 | 0.9873 | |
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| 0.3249 | 9.66 | 210 | 0.1890 | 0.9885 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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