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--- |
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license: apache-2.0 |
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base_model: facebook/convnext-tiny-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: finetuned-Leukemia-cell |
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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: 0.9661654135338346 |
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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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# finetuned-Leukemia-cell |
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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: 0.1249 |
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- Accuracy: 0.9662 |
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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: 0.0002 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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: 50 |
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- mixed_precision_training: Native AMP |
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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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| 0.3396 | 2.94 | 100 | 0.2611 | 0.9060 | |
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| 0.2488 | 5.88 | 200 | 0.2651 | 0.9173 | |
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| 0.1783 | 8.82 | 300 | 0.1906 | 0.9323 | |
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| 0.0837 | 11.76 | 400 | 0.1773 | 0.9511 | |
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| 0.0934 | 14.71 | 500 | 0.2027 | 0.9361 | |
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| 0.1283 | 17.65 | 600 | 0.0602 | 0.9737 | |
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| 0.06 | 20.59 | 700 | 0.1383 | 0.9624 | |
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| 0.024 | 23.53 | 800 | 0.0773 | 0.9737 | |
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| 0.0446 | 26.47 | 900 | 0.1669 | 0.9549 | |
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| 0.0342 | 29.41 | 1000 | 0.1320 | 0.9624 | |
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| 0.0458 | 32.35 | 1100 | 0.1128 | 0.9662 | |
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| 0.0394 | 35.29 | 1200 | 0.2099 | 0.9436 | |
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| 0.0593 | 38.24 | 1300 | 0.0890 | 0.9774 | |
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| 0.0346 | 41.18 | 1400 | 0.1216 | 0.9662 | |
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| 0.0535 | 44.12 | 1500 | 0.1303 | 0.9662 | |
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| 0.0139 | 47.06 | 1600 | 0.1195 | 0.9624 | |
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| 0.0476 | 50.0 | 1700 | 0.1249 | 0.9662 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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