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--- |
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license: apache-2.0 |
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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: convnext-tiny-224-drfx-surgery-classifier |
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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: 0.875 |
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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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# convnext-tiny-224-drfx-surgery-classifier |
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This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6160 |
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- Accuracy: 0.875 |
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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: 10 |
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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 | 1.0 | 4 | 0.7140 | 0.375 | |
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| No log | 2.0 | 8 | 0.6876 | 0.5 | |
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| 0.7104 | 3.0 | 12 | 0.6666 | 0.625 | |
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| 0.7104 | 4.0 | 16 | 0.6495 | 0.6875 | |
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| 0.6567 | 5.0 | 20 | 0.6360 | 0.75 | |
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| 0.6567 | 6.0 | 24 | 0.6247 | 0.8125 | |
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| 0.6567 | 7.0 | 28 | 0.6160 | 0.875 | |
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| 0.6277 | 8.0 | 32 | 0.6098 | 0.875 | |
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| 0.6277 | 9.0 | 36 | 0.6058 | 0.875 | |
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| 0.6122 | 10.0 | 40 | 0.6043 | 0.875 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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