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--- |
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license: other |
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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: mobilenet_v2_1.0_224-cxr-view |
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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: 0.929384965831435 |
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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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# mobilenet_v2_1.0_224-cxr-view |
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This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2278 |
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- Accuracy: 0.9294 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 30 |
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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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| 0.7049 | 1.0 | 109 | 0.6746 | 0.7449 | |
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| 0.6565 | 2.0 | 219 | 0.6498 | 0.6743 | |
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| 0.5699 | 3.0 | 328 | 0.5730 | 0.7995 | |
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| 0.5702 | 4.0 | 438 | 0.5119 | 0.8087 | |
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| 0.4849 | 5.0 | 547 | 0.4356 | 0.8679 | |
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| 0.356 | 6.0 | 657 | 0.4641 | 0.8087 | |
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| 0.3713 | 7.0 | 766 | 0.3407 | 0.8679 | |
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| 0.4571 | 8.0 | 876 | 0.4896 | 0.7813 | |
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| 0.3896 | 9.0 | 985 | 0.3124 | 0.8884 | |
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| 0.3422 | 10.0 | 1095 | 0.2791 | 0.9271 | |
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| 0.3358 | 11.0 | 1204 | 0.3998 | 0.8246 | |
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| 0.3658 | 12.0 | 1314 | 0.2716 | 0.9066 | |
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| 0.4547 | 13.0 | 1423 | 0.5828 | 0.7973 | |
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| 0.2615 | 14.0 | 1533 | 0.3446 | 0.8542 | |
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| 0.377 | 15.0 | 1642 | 0.6322 | 0.7312 | |
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| 0.2846 | 16.0 | 1752 | 0.2621 | 0.9248 | |
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| 0.3433 | 17.0 | 1861 | 0.3709 | 0.8383 | |
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| 0.2851 | 18.0 | 1971 | 0.8134 | 0.7312 | |
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| 0.2298 | 19.0 | 2080 | 0.4324 | 0.8314 | |
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| 0.3916 | 20.0 | 2190 | 0.3631 | 0.8360 | |
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| 0.3049 | 21.0 | 2299 | 0.3405 | 0.8633 | |
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| 0.3068 | 22.0 | 2409 | 0.2585 | 0.9021 | |
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| 0.3091 | 23.0 | 2518 | 0.2278 | 0.9294 | |
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| 0.2749 | 24.0 | 2628 | 0.2963 | 0.9043 | |
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| 0.3543 | 25.0 | 2737 | 0.2637 | 0.8975 | |
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| 0.3024 | 26.0 | 2847 | 0.2966 | 0.8998 | |
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| 0.2593 | 27.0 | 2956 | 0.3842 | 0.8542 | |
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| 0.1979 | 28.0 | 3066 | 0.2711 | 0.8884 | |
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| 0.2549 | 29.0 | 3175 | 0.3145 | 0.8633 | |
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| 0.3216 | 29.86 | 3270 | 0.4565 | 0.8155 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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