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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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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-gpu |
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results: [] |
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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-gpu |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1093 |
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- Accuracy: 0.9736 |
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- Confusion Matrix: [[60, 6], [0, 161]] |
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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: 1e-05 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 285 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Confusion Matrix | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------------:| |
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| 0.1208 | 1.7544 | 100 | 0.1628 | 0.9648 | [[58, 8], [0, 161]] | |
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| 0.0908 | 3.5088 | 200 | 0.1093 | 0.9736 | [[60, 6], [0, 161]] | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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