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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-tiny-22k-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: convnextv2-tiny-22k-224-finetuned-piid |
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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: val |
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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: 0.7853881278538812 |
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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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# convnextv2-tiny-22k-224-finetuned-piid |
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This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-224](https://huggingface.co/facebook/convnextv2-tiny-22k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6118 |
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- Accuracy: 0.7854 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 20 |
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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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| 1.2083 | 0.98 | 20 | 1.0137 | 0.6027 | |
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| 0.6826 | 2.0 | 41 | 0.6901 | 0.6895 | |
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| 0.5161 | 2.98 | 61 | 0.6377 | 0.7078 | |
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| 0.4475 | 4.0 | 82 | 0.5423 | 0.7215 | |
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| 0.4325 | 4.98 | 102 | 0.5165 | 0.7671 | |
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| 0.3433 | 6.0 | 123 | 0.5916 | 0.7763 | |
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| 0.2677 | 6.98 | 143 | 0.5866 | 0.7534 | |
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| 0.2498 | 8.0 | 164 | 0.5146 | 0.7900 | |
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| 0.2387 | 8.98 | 184 | 0.5631 | 0.7580 | |
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| 0.2132 | 10.0 | 205 | 0.5320 | 0.7991 | |
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| 0.2178 | 10.98 | 225 | 0.5833 | 0.7854 | |
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| 0.1474 | 12.0 | 246 | 0.5902 | 0.7900 | |
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| 0.1627 | 12.98 | 266 | 0.6142 | 0.7808 | |
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| 0.1651 | 14.0 | 287 | 0.6063 | 0.7808 | |
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| 0.158 | 14.98 | 307 | 0.6130 | 0.7808 | |
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| 0.126 | 16.0 | 328 | 0.6647 | 0.7671 | |
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| 0.0821 | 16.98 | 348 | 0.5972 | 0.7808 | |
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| 0.1062 | 18.0 | 369 | 0.5975 | 0.7945 | |
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| 0.1031 | 18.98 | 389 | 0.6129 | 0.7808 | |
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| 0.1268 | 19.51 | 400 | 0.6118 | 0.7854 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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