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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: microsoft/resnet-18 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: resnet-18-finetuned-papsmear |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9117647058823529 |
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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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# resnet-18-finetuned-papsmear |
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This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2838 |
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- Accuracy: 0.9118 |
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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: 50 |
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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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| No log | 0.9231 | 9 | 1.9256 | 0.1691 | |
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| 1.9692 | 1.9487 | 19 | 1.6557 | 0.2868 | |
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| 1.7979 | 2.9744 | 29 | 1.3300 | 0.5368 | |
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| 1.5079 | 4.0 | 39 | 1.0482 | 0.6324 | |
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| 1.217 | 4.9231 | 48 | 0.9019 | 0.6618 | |
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| 0.9536 | 5.9487 | 58 | 0.7687 | 0.6691 | |
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| 0.7881 | 6.9744 | 68 | 0.6150 | 0.7721 | |
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| 0.68 | 8.0 | 78 | 0.5481 | 0.7868 | |
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| 0.5678 | 8.9231 | 87 | 0.5341 | 0.7868 | |
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| 0.5169 | 9.9487 | 97 | 0.4800 | 0.7941 | |
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| 0.4838 | 10.9744 | 107 | 0.4356 | 0.8235 | |
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| 0.4738 | 12.0 | 117 | 0.4573 | 0.8162 | |
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| 0.3798 | 12.9231 | 126 | 0.4263 | 0.8088 | |
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| 0.3431 | 13.9487 | 136 | 0.4159 | 0.8382 | |
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| 0.3282 | 14.9744 | 146 | 0.3787 | 0.8603 | |
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| 0.3167 | 16.0 | 156 | 0.4234 | 0.8382 | |
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| 0.3186 | 16.9231 | 165 | 0.3853 | 0.8235 | |
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| 0.2568 | 17.9487 | 175 | 0.3904 | 0.8456 | |
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| 0.2528 | 18.9744 | 185 | 0.4013 | 0.8309 | |
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| 0.2661 | 20.0 | 195 | 0.3275 | 0.8824 | |
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| 0.2287 | 20.9231 | 204 | 0.3219 | 0.8824 | |
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| 0.2465 | 21.9487 | 214 | 0.3410 | 0.8529 | |
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| 0.2422 | 22.9744 | 224 | 0.3256 | 0.8603 | |
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| 0.222 | 24.0 | 234 | 0.3232 | 0.875 | |
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| 0.1917 | 24.9231 | 243 | 0.3307 | 0.8676 | |
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| 0.194 | 25.9487 | 253 | 0.3146 | 0.8971 | |
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| 0.212 | 26.9744 | 263 | 0.3125 | 0.8897 | |
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| 0.1718 | 28.0 | 273 | 0.3015 | 0.9044 | |
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| 0.1975 | 28.9231 | 282 | 0.3195 | 0.8824 | |
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| 0.1948 | 29.9487 | 292 | 0.3536 | 0.8971 | |
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| 0.1809 | 30.9744 | 302 | 0.3105 | 0.875 | |
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| 0.1744 | 32.0 | 312 | 0.3032 | 0.8824 | |
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| 0.1731 | 32.9231 | 321 | 0.2936 | 0.8971 | |
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| 0.1513 | 33.9487 | 331 | 0.2889 | 0.8824 | |
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| 0.1527 | 34.9744 | 341 | 0.2875 | 0.8897 | |
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| 0.1693 | 36.0 | 351 | 0.2754 | 0.8897 | |
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| 0.1743 | 36.9231 | 360 | 0.2875 | 0.8971 | |
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| 0.1463 | 37.9487 | 370 | 0.2961 | 0.8971 | |
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| 0.1429 | 38.9744 | 380 | 0.2848 | 0.8971 | |
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| 0.1483 | 40.0 | 390 | 0.2873 | 0.8897 | |
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| 0.1483 | 40.9231 | 399 | 0.2856 | 0.875 | |
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| 0.1613 | 41.9487 | 409 | 0.2801 | 0.8971 | |
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| 0.1358 | 42.9744 | 419 | 0.2838 | 0.9118 | |
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| 0.1453 | 44.0 | 429 | 0.2783 | 0.8971 | |
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| 0.1383 | 44.9231 | 438 | 0.2897 | 0.8897 | |
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| 0.1655 | 45.9487 | 448 | 0.2847 | 0.9044 | |
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| 0.1489 | 46.1538 | 450 | 0.2861 | 0.8897 | |
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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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