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README.md
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@@ -31,15 +31,18 @@ This model is a fine-tuned version of [google/efficientnet-b5](https://huggingfa
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It achieves the following results on the evaluation set:
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- Loss: 0.9410
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- Accuracy: 0.8020
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<div style="text-align: center;">
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<h2>
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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| 1.3872 | 1.0 | 180 | 1.0601 | 0.6853 | 0.6485 | 0.6853 | 0.6550 | 0.6853 | 0.6853 | 0.6802 | 0.8177 | 0.6853 | 0.8330 |
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| 1.3872 | 2.0 | 360 | 0.9533 | 0.7843 | 0.7483 | 0.7843 | 0.7548 | 0.7843 | 0.7843 | 0.7819 | 0.8354 | 0.7843 | 0.8471 |
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It achieves the following results on the evaluation set:
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- Loss: 0.9410
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- Accuracy: 0.8020
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- F1
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- Weighted: 0.7736
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- Micro: 0.8020
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- Macro: 0.7802
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- Recall
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- Weighted: 0.8020
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- Micro: 0.8020
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- Macro: 0.7977
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- Precision
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- Weighted: 0.8535
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- Micro: 0.8020
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- Macro: 0.8682
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<div style="text-align: center;">
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<h2>
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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| 1.3872 | 1.0 | 180 | 1.0601 | 0.6853 | 0.6485 | 0.6853 | 0.6550 | 0.6853 | 0.6853 | 0.6802 | 0.8177 | 0.6853 | 0.8330 |
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| 1.3872 | 2.0 | 360 | 0.9533 | 0.7843 | 0.7483 | 0.7843 | 0.7548 | 0.7843 | 0.7843 | 0.7819 | 0.8354 | 0.7843 | 0.8471 |
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