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--- |
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library_name: transformers |
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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 |
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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 |
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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: 1.3177 |
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- Accuracy: 0.4987 |
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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: 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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| 1.6698 | 1.0 | 48 | 1.5900 | 0.2539 | |
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| 1.4981 | 2.0 | 96 | 1.4551 | 0.3835 | |
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| 1.2747 | 3.0 | 144 | 1.3591 | 0.4408 | |
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| 1.0701 | 4.0 | 192 | 1.3058 | 0.4902 | |
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| 0.7885 | 5.0 | 240 | 1.3177 | 0.4987 | |
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| 0.6023 | 6.0 | 288 | 1.3985 | 0.4870 | |
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| 0.4814 | 7.0 | 336 | 1.4607 | 0.4824 | |
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| 0.3708 | 8.0 | 384 | 1.5195 | 0.4720 | |
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| 0.2755 | 9.0 | 432 | 1.5524 | 0.4798 | |
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| 0.2476 | 10.0 | 480 | 1.5632 | 0.4792 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Tokenizers 0.19.1 |
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