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--- |
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license: other |
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base_model: google/mobilenet_v2_1.4_224 |
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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-Retinopathy |
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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: 0.9306930693069307 |
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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-Retinopathy |
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This model is a fine-tuned version of [google/mobilenet_v2_1.4_224](https://huggingface.co/google/mobilenet_v2_1.4_224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2044 |
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- Accuracy: 0.9307 |
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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: 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: 15 |
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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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| 0.4403 | 1.0 | 113 | 0.5330 | 0.7079 | |
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| 0.5538 | 2.0 | 227 | 0.4312 | 0.7723 | |
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| 0.542 | 3.0 | 340 | 0.5137 | 0.7426 | |
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| 0.4776 | 4.0 | 454 | 0.4656 | 0.7723 | |
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| 0.4244 | 5.0 | 567 | 1.0400 | 0.5990 | |
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| 0.4694 | 6.0 | 681 | 0.5936 | 0.7228 | |
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| 0.4494 | 7.0 | 794 | 0.4667 | 0.7822 | |
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| 0.4647 | 8.0 | 908 | 0.2629 | 0.8960 | |
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| 0.3646 | 9.0 | 1021 | 0.2287 | 0.8861 | |
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| 0.4827 | 10.0 | 1135 | 1.7967 | 0.5149 | |
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| 0.3679 | 11.0 | 1248 | 0.4184 | 0.8267 | |
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| 0.3454 | 12.0 | 1362 | 0.1885 | 0.9406 | |
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| 0.3562 | 13.0 | 1475 | 0.2798 | 0.9059 | |
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| 0.3397 | 14.0 | 1589 | 1.6444 | 0.5891 | |
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| 0.4047 | 14.93 | 1695 | 0.2044 | 0.9307 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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