Studying Impact of Batch Size and Mixed Precision
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This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
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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0.1688 | 1.0 | 165 | 0.0092 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
0.0103 | 2.0 | 330 | 0.0262 | 0.9909 | 0.9909 | 0.9909 | 0.9907 | 0.9909 | 0.9909 | 0.9906 | 0.9911 | 0.9909 | 0.9910 |
0.0028 | 3.0 | 495 | 0.0014 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
0.001 | 4.0 | 660 | 0.0020 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
0.0007 | 5.0 | 825 | 0.0016 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |