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README.md
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@@ -24,14 +24,31 @@ This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/
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It achieves the following results on the evaluation set:
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- Loss: 0.0949
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- Loc
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Loc
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| 0.1119 | 1.0 | 5795 | 0.1067
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| 0.0724 | 2.0 | 11590 | 0.0949
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### Framework versions
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It achieves the following results on the evaluation set:
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- Loss: 0.0949
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- Loc
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- Precision: 0.9289891395154553
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- Recall: 0.9336691855583543
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- F1: 0.931323283082077
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- Number: 5955
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- Misc
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- Precision: 0.8191960332920134
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- Recall: 0.9140486069946651
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- F1: 0.8640268957788569
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- Number: 5061
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- Org
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- Precision: 0.9199886104783599
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- Recall: 0.9367932734125833
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- F1: 0.9283148972848728
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- Number: 3449
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- Per
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- Precision: 0.9687377113645301
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- Recall: 0.9456813819577735
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- F1: 0.9570707070707071
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- Number: 5210
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- Overall
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- Precision: 0.9068
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- Recall: 0.9324
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- F1: 0.9194
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- Accuracy: 0.9904
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Loc Precision | Loc Recall | Loc F1 | Loc Number | Misc Precision | Misc Recall | Misc F1 | Misc Number | Org Precision | Org Recall | Org F1 | Org Number | Per Precision | Per Recall | Per F1 | Per Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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|:-------------:|:-----:|:-----:|:--------------:|:-----------------:|:-------------:|:------------:|:--------------:|:-----------------:|:--------------:|:----------:|:--------:|:--------:|:----------:|:-----------:|:----------:|:----------:|:----------:|:---------:|:----------:|:---------:|:-------:|:----------:|:---------:|
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| 0.1119 | 1.0 | 5795 | 0.1067 | 0.9054 | 0.9382 | 0.9215 | 5955 | 0.7967 | 0.8884 | 0.8401 | 5061 | 0.9112 | 0.9226 | 0.9169 | 3449 | 0.9585 | 0.9524 | 0.9554 | 5210 | 0.8899 | 0.9264 | 0.9078 | 0.9887 |
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| 0.0724 | 2.0 | 11590 | 0.0949 | 0.9290 | 0.9337 | 0.9313 | 5955 | 0.8192 | 0.9140 | 0.8640 | 5061 | 0.9200 | 0.9368 | 0.9283 | 3449 | 0.9687 | 0.9457 | 0.9571 | 5210 | 0.9068 | 0.9324 | 0.9194 | 0.9904 |
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* All values in the above chart are rounded to the nearest ten-thousandths.
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### Framework versions
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