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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0.1131 | 1.0 | 329 | 0.0040 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
0.0058 | 2.0 | 658 | 0.0063 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 |
0.0013 | 3.0 | 987 | 0.0061 | 0.9985 | 0.9985 | 0.9985 | 0.9984 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9984 |
0.0003 | 4.0 | 1316 | 0.0036 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
0.0002 | 5.0 | 1645 | 0.0037 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |