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--- |
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library_name: transformers |
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base_model: RobertZ2011/resnet-18-birb |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: klasifikasiburung |
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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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# klasifikasiburung |
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This model is a fine-tuned version of [RobertZ2011/resnet-18-birb](https://huggingface.co/RobertZ2011/resnet-18-birb) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0186 |
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- Accuracy: 0.7565 |
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- Precision: 0.7631 |
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- Recall: 0.7565 |
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- F1: 0.7554 |
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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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- 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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.5955 | 1.0 | 188 | 1.4442 | 0.7235 | 0.7426 | 0.7235 | 0.7169 | |
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| 1.1224 | 2.0 | 376 | 1.2881 | 0.7458 | 0.7546 | 0.7458 | 0.7406 | |
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| 0.7778 | 3.0 | 564 | 1.1965 | 0.7501 | 0.7635 | 0.7501 | 0.7483 | |
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| 0.5573 | 4.0 | 752 | 1.1417 | 0.7565 | 0.7635 | 0.7565 | 0.7538 | |
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| 0.4231 | 5.0 | 940 | 1.1077 | 0.7584 | 0.7671 | 0.7584 | 0.7567 | |
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| 0.2878 | 6.0 | 1128 | 1.0893 | 0.7601 | 0.7716 | 0.7601 | 0.7597 | |
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| 0.2043 | 7.0 | 1316 | 1.0688 | 0.7591 | 0.7661 | 0.7591 | 0.7579 | |
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| 0.1326 | 8.0 | 1504 | 1.0687 | 0.7582 | 0.7653 | 0.7582 | 0.7565 | |
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| 0.0851 | 9.0 | 1692 | 1.0502 | 0.7598 | 0.7652 | 0.7598 | 0.7581 | |
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| 0.0807 | 10.0 | 1880 | 1.0318 | 0.7582 | 0.7644 | 0.7582 | 0.7569 | |
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| 0.0581 | 11.0 | 2068 | 1.0403 | 0.7572 | 0.7629 | 0.7572 | 0.7558 | |
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| 0.043 | 12.0 | 2256 | 1.0295 | 0.7565 | 0.7633 | 0.7565 | 0.7557 | |
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| 0.0379 | 13.0 | 2444 | 1.0271 | 0.7568 | 0.7636 | 0.7568 | 0.7557 | |
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| 0.0399 | 14.0 | 2632 | 1.0319 | 0.7558 | 0.7627 | 0.7558 | 0.7549 | |
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| 0.0447 | 15.0 | 2820 | 1.0186 | 0.7565 | 0.7631 | 0.7565 | 0.7554 | |
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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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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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