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gcperk20
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convnext-small-224-finetuned-piid

Image Classification
Transformers
PyTorch
convnext
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/convnext-small-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: convnext-small-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: 0.7579908675799086
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+ ---
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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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+
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+ # convnext-small-224-finetuned-piid
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+
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+ This model is a fine-tuned version of [facebook/convnext-small-224](https://huggingface.co/facebook/convnext-small-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6131
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+ - Accuracy: 0.7580
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.3405 | 0.98 | 20 | 1.3201 | 0.4155 |
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+ | 1.1715 | 2.0 | 41 | 1.1362 | 0.5708 |
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+ | 0.9231 | 2.98 | 61 | 0.9255 | 0.6438 |
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+ | 0.7128 | 4.0 | 82 | 0.7558 | 0.6986 |
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+ | 0.6204 | 4.98 | 102 | 0.7056 | 0.7534 |
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+ | 0.5322 | 6.0 | 123 | 0.6610 | 0.7397 |
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+ | 0.4403 | 6.98 | 143 | 0.6639 | 0.7443 |
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+ | 0.4388 | 8.0 | 164 | 0.6472 | 0.7306 |
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+ | 0.3901 | 8.98 | 184 | 0.6684 | 0.7352 |
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+ | 0.4202 | 10.0 | 205 | 0.5934 | 0.7397 |
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+ | 0.3784 | 10.98 | 225 | 0.5651 | 0.7626 |
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+ | 0.2973 | 12.0 | 246 | 0.6439 | 0.7580 |
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+ | 0.3614 | 12.98 | 266 | 0.5844 | 0.7534 |
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+ | 0.2795 | 14.0 | 287 | 0.6015 | 0.7306 |
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+ | 0.2825 | 14.98 | 307 | 0.6031 | 0.7626 |
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+ | 0.2364 | 16.0 | 328 | 0.6249 | 0.7534 |
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+ | 0.2162 | 16.98 | 348 | 0.6248 | 0.7626 |
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+ | 0.2455 | 18.0 | 369 | 0.6153 | 0.7489 |
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+ | 0.2314 | 18.98 | 389 | 0.6113 | 0.7580 |
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+ | 0.248 | 19.51 | 400 | 0.6131 | 0.7580 |
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+
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+
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+ ### Framework versions
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+
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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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