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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: finetuned-mango-types |
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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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# finetuned-mango-types |
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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: 0.5751 |
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- Accuracy: 0.9292 |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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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- 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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| 1.9926 | 1.0 | 22 | 1.9526 | 0.3833 | |
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| 1.7976 | 2.0 | 44 | 1.7500 | 0.6083 | |
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| 1.5678 | 3.0 | 66 | 1.5025 | 0.7583 | |
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| 1.3907 | 4.0 | 88 | 1.2804 | 0.9 | |
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| 1.0873 | 5.0 | 110 | 1.1005 | 0.9042 | |
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| 0.9511 | 6.0 | 132 | 1.0130 | 0.8875 | |
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| 0.8476 | 7.0 | 154 | 0.9424 | 0.8833 | |
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| 0.7511 | 8.0 | 176 | 0.8325 | 0.9042 | |
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| 0.6985 | 9.0 | 198 | 0.7894 | 0.9083 | |
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| 0.6515 | 10.0 | 220 | 0.8052 | 0.8792 | |
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| 0.5775 | 11.0 | 242 | 0.7600 | 0.8792 | |
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| 0.5458 | 12.0 | 264 | 0.6684 | 0.925 | |
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| 0.5331 | 13.0 | 286 | 0.7148 | 0.8917 | |
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| 0.4823 | 14.0 | 308 | 0.6849 | 0.9125 | |
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| 0.4579 | 15.0 | 330 | 0.6414 | 0.9167 | |
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| 0.4435 | 16.0 | 352 | 0.6557 | 0.8833 | |
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| 0.4411 | 17.0 | 374 | 0.5968 | 0.9083 | |
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| 0.453 | 18.0 | 396 | 0.5751 | 0.9292 | |
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| 0.445 | 19.0 | 418 | 0.6035 | 0.9083 | |
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| 0.4357 | 20.0 | 440 | 0.6010 | 0.9083 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
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