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bert-base-multilingual-cased

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README.md CHANGED
@@ -16,16 +16,16 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-base-multilingual-cased
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- This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3054
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- - F1 Macro: 0.8821
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- - F1: 0.9191
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- - F1 Neg: 0.8452
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- - Acc: 0.8938
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- - Prec: 0.9130
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- - Recall: 0.9253
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- - Mcc: 0.7645
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  ## Model description
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@@ -56,23 +56,23 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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- | 0.505 | 1.0 | 800 | 0.3804 | 0.8285 | 0.8856 | 0.7715 | 0.8475 | 0.8489 | 0.9255 | 0.6639 |
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- | 0.3286 | 2.0 | 1600 | 0.3744 | 0.8564 | 0.9006 | 0.8123 | 0.87 | 0.8787 | 0.9235 | 0.7150 |
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- | 0.2764 | 3.0 | 2400 | 0.6199 | 0.8398 | 0.8949 | 0.7848 | 0.8588 | 0.8513 | 0.9431 | 0.6897 |
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- | 0.1761 | 4.0 | 3200 | 0.6083 | 0.8506 | 0.8990 | 0.8022 | 0.8662 | 0.8670 | 0.9333 | 0.7061 |
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- | 0.1235 | 5.0 | 4000 | 0.8350 | 0.8516 | 0.8962 | 0.8071 | 0.865 | 0.8792 | 0.9137 | 0.7046 |
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- | 0.0508 | 6.0 | 4800 | 0.8916 | 0.8425 | 0.8822 | 0.8027 | 0.8525 | 0.8984 | 0.8667 | 0.6859 |
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- | 0.0386 | 7.0 | 5600 | 1.0909 | 0.8488 | 0.8983 | 0.7993 | 0.865 | 0.8641 | 0.9353 | 0.7033 |
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- | 0.0255 | 8.0 | 6400 | 1.1529 | 0.8464 | 0.8853 | 0.8074 | 0.8562 | 0.9006 | 0.8706 | 0.6936 |
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- | 0.0276 | 9.0 | 7200 | 1.2287 | 0.8499 | 0.8955 | 0.8043 | 0.8638 | 0.8762 | 0.9157 | 0.7015 |
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- | 0.0229 | 10.0 | 8000 | 1.1899 | 0.8440 | 0.8854 | 0.8027 | 0.855 | 0.8924 | 0.8784 | 0.6883 |
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- | 0.0127 | 11.0 | 8800 | 1.2131 | 0.8521 | 0.8958 | 0.8085 | 0.865 | 0.8821 | 0.9098 | 0.7051 |
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- | 0.0091 | 12.0 | 9600 | 1.3365 | 0.8515 | 0.8896 | 0.8134 | 0.8612 | 0.9030 | 0.8765 | 0.7037 |
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- | 0.0073 | 13.0 | 10400 | 1.3723 | 0.8492 | 0.8895 | 0.8089 | 0.86 | 0.8948 | 0.8843 | 0.6985 |
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- | 0.0083 | 14.0 | 11200 | 1.4210 | 0.8465 | 0.8876 | 0.8055 | 0.8575 | 0.8929 | 0.8824 | 0.6931 |
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- | 0.0 | 15.0 | 12000 | 1.4425 | 0.8434 | 0.8882 | 0.7986 | 0.8562 | 0.8805 | 0.8961 | 0.6871 |
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  ### Framework versions
 
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  # bert-base-multilingual-cased
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8104
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+ - F1 Macro: 0.9046
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+ - F1: 0.9361
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+ - F1 Neg: 0.8731
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+ - Acc: 0.915
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+ - Prec: 0.9468
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+ - Recall: 0.9257
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+ - Mcc: 0.8097
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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+ | No log | 1.0 | 400 | 0.5310 | 0.7579 | 0.8675 | 0.6484 | 0.8075 | 0.7754 | 0.9844 | 0.5871 |
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+ | 0.44 | 2.0 | 800 | 0.5080 | 0.8761 | 0.9176 | 0.8346 | 0.89 | 0.8813 | 0.9570 | 0.7588 |
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+ | 0.296 | 3.0 | 1200 | 0.4352 | 0.8610 | 0.9010 | 0.8211 | 0.8725 | 0.8958 | 0.9062 | 0.7221 |
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+ | 0.177 | 4.0 | 1600 | 0.4961 | 0.8677 | 0.9037 | 0.8316 | 0.8775 | 0.9091 | 0.8984 | 0.7355 |
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+ | 0.0941 | 5.0 | 2000 | 0.6030 | 0.8872 | 0.9213 | 0.8530 | 0.8975 | 0.9057 | 0.9375 | 0.7754 |
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+ | 0.0941 | 6.0 | 2400 | 0.6556 | 0.8839 | 0.9236 | 0.8441 | 0.8975 | 0.8826 | 0.9688 | 0.7765 |
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+ | 0.0615 | 7.0 | 2800 | 0.6839 | 0.8852 | 0.9142 | 0.8562 | 0.8925 | 0.9347 | 0.8945 | 0.7719 |
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+ | 0.0436 | 8.0 | 3200 | 0.6418 | 0.8938 | 0.9283 | 0.8593 | 0.905 | 0.8978 | 0.9609 | 0.7920 |
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+ | 0.0288 | 9.0 | 3600 | 0.7248 | 0.8908 | 0.9266 | 0.8550 | 0.9025 | 0.8945 | 0.9609 | 0.7866 |
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+ | 0.0137 | 10.0 | 4000 | 0.8190 | 0.8889 | 0.9198 | 0.8581 | 0.8975 | 0.9216 | 0.9180 | 0.7779 |
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+ | 0.0137 | 11.0 | 4400 | 0.7969 | 0.8937 | 0.9243 | 0.8632 | 0.9025 | 0.9189 | 0.9297 | 0.7875 |
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+ | 0.0033 | 12.0 | 4800 | 0.9380 | 0.8839 | 0.9236 | 0.8441 | 0.8975 | 0.8826 | 0.9688 | 0.7765 |
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+ | 0.0003 | 13.0 | 5200 | 0.8792 | 0.8940 | 0.9240 | 0.8641 | 0.9025 | 0.9222 | 0.9258 | 0.7881 |
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+ | 0.0 | 14.0 | 5600 | 0.8880 | 0.8998 | 0.9276 | 0.8720 | 0.9075 | 0.9294 | 0.9258 | 0.7996 |
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+ | 0.0042 | 15.0 | 6000 | 0.8816 | 0.8972 | 0.9255 | 0.8690 | 0.905 | 0.9291 | 0.9219 | 0.7945 |
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  ### Framework versions
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