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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1830
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- - Accuracy: 0.9395
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- - Precision: 0.9404
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- - Recall: 0.9397
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- - F1: 0.9397
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  ## Model description
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@@ -58,11 +58,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.6401 | 1.0 | 250 | 0.4404 | 0.8739 | 0.8776 | 0.8746 | 0.8741 |
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- | 0.4281 | 2.0 | 500 | 0.2785 | 0.9195 | 0.9221 | 0.9197 | 0.9198 |
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- | 0.3803 | 3.0 | 750 | 0.2285 | 0.9245 | 0.9268 | 0.9251 | 0.9249 |
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- | 0.3044 | 4.0 | 1000 | 0.1969 | 0.9360 | 0.9379 | 0.9357 | 0.9362 |
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- | 0.2596 | 5.0 | 1250 | 0.1830 | 0.9395 | 0.9404 | 0.9397 | 0.9397 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1862
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+ - Accuracy: 0.9400
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+ - Precision: 0.9412
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+ - Recall: 0.9401
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+ - F1: 0.9403
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.6303 | 1.0 | 250 | 0.4444 | 0.8729 | 0.8811 | 0.8735 | 0.8734 |
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+ | 0.4303 | 2.0 | 500 | 0.2761 | 0.9135 | 0.9162 | 0.9136 | 0.9136 |
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+ | 0.3779 | 3.0 | 750 | 0.2324 | 0.9245 | 0.9263 | 0.9252 | 0.9248 |
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+ | 0.3067 | 4.0 | 1000 | 0.1997 | 0.9360 | 0.9378 | 0.9358 | 0.9363 |
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+ | 0.2619 | 5.0 | 1250 | 0.1862 | 0.9400 | 0.9412 | 0.9401 | 0.9403 |
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  ### Framework versions