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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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- image-classification |
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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-melSpecImagesCREMA |
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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-melSpecImagesCREMA |
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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 Supreeta03/CREMA-melSpecImages dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1416 |
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- Accuracy: 0.5808 |
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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: 0.0002 |
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- train_batch_size: 32 |
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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: 10 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.5606 | 0.76 | 100 | 1.4424 | 0.4079 | |
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| 1.2841 | 1.53 | 200 | 1.4981 | 0.3695 | |
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| 1.0159 | 2.29 | 300 | 1.1693 | 0.5518 | |
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| 0.9868 | 3.05 | 400 | 1.0969 | 0.5931 | |
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| 0.8477 | 3.82 | 500 | 1.1719 | 0.5797 | |
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| 0.5495 | 4.58 | 600 | 1.2348 | 0.5806 | |
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| 0.2671 | 5.34 | 700 | 1.3457 | 0.5854 | |
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| 0.1388 | 6.11 | 800 | 1.3891 | 0.5787 | |
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| 0.1548 | 6.87 | 900 | 1.4216 | 0.5979 | |
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| 0.0906 | 7.63 | 1000 | 1.6401 | 0.5643 | |
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| 0.1047 | 8.4 | 1100 | 1.6780 | 0.5873 | |
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| 0.0583 | 9.16 | 1200 | 1.6795 | 0.5768 | |
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| 0.0228 | 9.92 | 1300 | 1.6926 | 0.5883 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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