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---
language:
- de
- fr
- it
pipeline_tag: token-classification
license: cc-by-sa-4.0
---
# Tagset
- O
- B-CITATION
- I-CITATION
- B-LAW
- I-LAW
# Training
- The model was trained with the following hyperparamters:
- batch size: 64
- learning_rate: 0.00001
- number of training epochs: 50 (actually trained: 23)
- early stopping patience: 5
# Predict scores
| \bf metric | \bf score |
|---------------------------------|--------------------|
| de_predict/_CITATION_f1 | 0.9793131792857794 |
| de_predict/_CITATION_precision | 0.9852522282458881 |
| de_predict/_CITATION_recall | 0.9734453018610985 |
| de_predict/_LAW_f1 | 0.9207842961099632 |
| de_predict/_LAW_precision | 0.8598544432559407 |
| de_predict/_LAW_recall | 0.9910077594333921 |
| de_predict/_accuracy_normalized | 0.9880353522464387 |
| de_predict/_macro-f1 | 0.9504272924171073 |
| de_predict/_macro-precision | 0.9822265306472453 |
| de_predict/_macro-recall | 0.9232171398568052 |
| de_predict/_micro-f1 | 0.9405898834091524 |
| de_predict/_micro-precision | 0.9849051246865093 |
| de_predict/_micro-recall | 0.9000908134288556 |
| de_predict/_steps_per_second | 0.549 |
| de_predict/_weighted-f1 | 0.939658320951984 |
| de_predict/_weighted-precision | 0.9854977355183103 |
| de_predict/_weighted-recall | 0.9000908134288556 |
| fr_predict/_CITATION_f1 | 0.9554686901203342 |
| fr_predict/_CITATION_precision | 0.9684586699813549 |
| fr_predict/_CITATION_recall | 0.9428225684465286 |
| fr_predict/_LAW_f1 | 0.910095519316377 |
| fr_predict/_LAW_precision | 0.8366717393986756 |
| fr_predict/_LAW_recall | 0.9976459048553212 |
| fr_predict/_accuracy_normalized | 0.9830767480044869 |
| fr_predict/_macro-f1 | 0.9330080903677362 |
| fr_predict/_macro-precision | 0.9702342366509249 |
| fr_predict/_macro-recall | 0.9029739799827206 |
| fr_predict/_micro-f1 | 0.920617324580396 |
| fr_predict/_micro-precision | 0.9842228065627199 |
| fr_predict/_micro-recall | 0.8647338279317974 |
| fr_predict/_steps_per_second | 0.593 |
| fr_predict/_weighted-f1 | 0.9198669665372888 |
| fr_predict/_weighted-precision | 0.9861681830521788 |
| fr_predict/_weighted-recall | 0.8647338279317974 |
| it_predict/_CITATION_f1 | 0.9703896103896105 |
| it_predict/_CITATION_precision | 0.9769874476987448 |
| it_predict/_CITATION_recall | 0.9638802889576883 |
| it_predict/_LAW_f1 | 0.9099276791584483 |
| it_predict/_LAW_precision | 0.8422590068159689 |
| it_predict/_LAW_recall | 0.9894195024306548 |
| it_predict/_accuracy_normalized | 0.9892137683075134 |
| it_predict/_macro-f1 | 0.9413484848298093 |
| it_predict/_macro-precision | 0.9766498956941716 |
| it_predict/_macro-recall | 0.9119834901073706 |
| it_predict/_micro-f1 | 0.9311429570080392 |
| it_predict/_micro-precision | 0.9803127874885005 |
| it_predict/_micro-recall | 0.8866699950074888 |
| it_predict/_steps_per_second | 0.563 |
| it_predict/_weighted-f1 | 0.929971077318579 |
| it_predict/_weighted-precision | 0.9813271971464931 |
| it_predict/_weighted-recall | 0.8866699950074888 |
| predict/_CITATION_f1 | 0.973621340187501 |
| predict/_CITATION_precision | 0.981138340970977 |
| predict/_CITATION_recall | 0.9662186467837405 |
| predict/_LAW_f1 | 0.9168199439712499 |
| predict/_LAW_precision | 0.8514980289093298 |
| predict/_LAW_recall | 0.9929968125536349 |
| predict/_accuracy_normalized | 0.986841752305624 |
| predict/_macro-f1 | 0.9455976917351873 |
| predict/_macro-precision | 0.9796077296686877 |
| predict/_macro-recall | 0.9169959471957758 |
| predict/_micro-f1 | 0.934344809828224 |
| predict/_micro-precision | 0.9844524443053164 |
| predict/_micro-recall | 0.8890909776278342 |
| predict/_steps_per_second | 0.557 |
| predict/_weighted-f1 | 0.9333974918752409 |
| predict/_weighted-precision | 0.9854002360022739 |
| predict/_weighted-recall | 0.8890909776278342 |
| predict_samples | 28218 |
|