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MiniLM-swiss_citation_extraction-de-fr-it

Token Classification
Transformers
PyTorch
Safetensors
German
French
Italian
bert
Inference Endpoints
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kapllan commited on
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1 Parent(s): 5bb08e1

Update README.md

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Rounded the scores of the metric values.

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  1. README.md +72 -71
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@@ -23,74 +23,75 @@ license: cc-by-sa-4.0
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  # Predict scores
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- | \bf metric | \bf score |
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- |---------------------------------|--------------------|
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- | de_predict/_CITATION_f1 | 0.9793131792857794 |
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- | de_predict/_CITATION_precision | 0.9852522282458881 |
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- | de_predict/_CITATION_recall | 0.9734453018610985 |
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- | de_predict/_LAW_f1 | 0.9207842961099632 |
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- | de_predict/_LAW_precision | 0.8598544432559407 |
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- | de_predict/_LAW_recall | 0.9910077594333921 |
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- | de_predict/_accuracy_normalized | 0.9880353522464387 |
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- | de_predict/_macro-f1 | 0.9504272924171073 |
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- | de_predict/_macro-precision | 0.9822265306472453 |
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- | de_predict/_macro-recall | 0.9232171398568052 |
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- | de_predict/_micro-f1 | 0.9405898834091524 |
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- | de_predict/_micro-precision | 0.9849051246865093 |
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- | de_predict/_micro-recall | 0.9000908134288556 |
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- | de_predict/_steps_per_second | 0.549 |
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- | de_predict/_weighted-f1 | 0.939658320951984 |
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- | de_predict/_weighted-precision | 0.9854977355183103 |
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- | de_predict/_weighted-recall | 0.9000908134288556 |
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- | fr_predict/_CITATION_f1 | 0.9554686901203342 |
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- | fr_predict/_CITATION_precision | 0.9684586699813549 |
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- | fr_predict/_CITATION_recall | 0.9428225684465286 |
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- | fr_predict/_LAW_f1 | 0.910095519316377 |
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- | fr_predict/_LAW_precision | 0.8366717393986756 |
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- | fr_predict/_LAW_recall | 0.9976459048553212 |
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- | fr_predict/_accuracy_normalized | 0.9830767480044869 |
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- | fr_predict/_macro-f1 | 0.9330080903677362 |
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- | fr_predict/_macro-precision | 0.9702342366509249 |
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- | fr_predict/_macro-recall | 0.9029739799827206 |
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- | fr_predict/_micro-f1 | 0.920617324580396 |
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- | fr_predict/_micro-precision | 0.9842228065627199 |
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- | fr_predict/_micro-recall | 0.8647338279317974 |
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- | fr_predict/_steps_per_second | 0.593 |
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- | fr_predict/_weighted-f1 | 0.9198669665372888 |
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- | fr_predict/_weighted-precision | 0.9861681830521788 |
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- | fr_predict/_weighted-recall | 0.8647338279317974 |
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- | it_predict/_CITATION_f1 | 0.9703896103896105 |
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- | it_predict/_CITATION_precision | 0.9769874476987448 |
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- | it_predict/_CITATION_recall | 0.9638802889576883 |
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- | it_predict/_LAW_f1 | 0.9099276791584483 |
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- | it_predict/_LAW_precision | 0.8422590068159689 |
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- | it_predict/_LAW_recall | 0.9894195024306548 |
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- | it_predict/_accuracy_normalized | 0.9892137683075134 |
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- | it_predict/_macro-f1 | 0.9413484848298093 |
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- | it_predict/_macro-precision | 0.9766498956941716 |
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- | it_predict/_macro-recall | 0.9119834901073706 |
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- | it_predict/_micro-f1 | 0.9311429570080392 |
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- | it_predict/_micro-precision | 0.9803127874885005 |
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- | it_predict/_micro-recall | 0.8866699950074888 |
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- | it_predict/_steps_per_second | 0.563 |
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- | it_predict/_weighted-f1 | 0.929971077318579 |
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- | it_predict/_weighted-precision | 0.9813271971464931 |
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- | it_predict/_weighted-recall | 0.8866699950074888 |
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- | predict/_CITATION_f1 | 0.973621340187501 |
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- | predict/_CITATION_precision | 0.981138340970977 |
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- | predict/_CITATION_recall | 0.9662186467837405 |
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- | predict/_LAW_f1 | 0.9168199439712499 |
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- | predict/_LAW_precision | 0.8514980289093298 |
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- | predict/_LAW_recall | 0.9929968125536349 |
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- | predict/_accuracy_normalized | 0.986841752305624 |
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- | predict/_macro-f1 | 0.9455976917351873 |
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- | predict/_macro-precision | 0.9796077296686877 |
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- | predict/_macro-recall | 0.9169959471957758 |
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- | predict/_micro-f1 | 0.934344809828224 |
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- | predict/_micro-precision | 0.9844524443053164 |
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- | predict/_micro-recall | 0.8890909776278342 |
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- | predict/_steps_per_second | 0.557 |
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- | predict/_weighted-f1 | 0.9333974918752409 |
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- | predict/_weighted-precision | 0.9854002360022739 |
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- | predict/_weighted-recall | 0.8890909776278342 |
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- | predict_samples | 28218 |
 
 
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  # Predict scores
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+ | **metric** | **score** |
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+ |---------------------------------|-------|
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+ | de_predict/_CITATION_f1 | 97.93 |
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+ | de_predict/_CITATION_precision | 98.53 |
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+ | de_predict/_CITATION_recall | 97.34 |
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+ | de_predict/_LAW_f1 | 92.08 |
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+ | de_predict/_LAW_precision | 85.99 |
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+ | de_predict/_LAW_recall | 99.1 |
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+ | de_predict/_accuracy_normalized | 98.8 |
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+ | de_predict/_macro-f1 | 95.04 |
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+ | de_predict/_macro-precision | 98.22 |
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+ | de_predict/_macro-recall | 92.32 |
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+ | de_predict/_micro-f1 | 94.06 |
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+ | de_predict/_micro-precision | 98.49 |
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+ | de_predict/_micro-recall | 90.01 |
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+ | de_predict/_steps_per_second | 54.9 |
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+ | de_predict/_weighted-f1 | 93.97 |
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+ | de_predict/_weighted-precision | 98.55 |
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+ | de_predict/_weighted-recall | 90.01 |
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+ | fr_predict/_CITATION_f1 | 95.55 |
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+ | fr_predict/_CITATION_precision | 96.85 |
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+ | fr_predict/_CITATION_recall | 94.28 |
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+ | fr_predict/_LAW_f1 | 91.01 |
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+ | fr_predict/_LAW_precision | 83.67 |
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+ | fr_predict/_LAW_recall | 99.76 |
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+ | fr_predict/_accuracy_normalized | 98.31 |
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+ | fr_predict/_macro-f1 | 93.3 |
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+ | fr_predict/_macro-precision | 97.02 |
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+ | fr_predict/_macro-recall | 90.3 |
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+ | fr_predict/_micro-f1 | 92.06 |
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+ | fr_predict/_micro-precision | 98.42 |
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+ | fr_predict/_micro-recall | 86.47 |
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+ | fr_predict/_steps_per_second | 59.3 |
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+ | fr_predict/_weighted-f1 | 91.99 |
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+ | fr_predict/_weighted-precision | 98.62 |
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+ | fr_predict/_weighted-recall | 86.47 |
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+ | it_predict/_CITATION_f1 | 97.04 |
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+ | it_predict/_CITATION_precision | 97.7 |
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+ | it_predict/_CITATION_recall | 96.39 |
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+ | it_predict/_LAW_f1 | 90.99 |
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+ | it_predict/_LAW_precision | 84.23 |
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+ | it_predict/_LAW_recall | 98.94 |
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+ | it_predict/_accuracy_normalized | 98.92 |
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+ | it_predict/_macro-f1 | 94.13 |
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+ | it_predict/_macro-precision | 97.66 |
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+ | it_predict/_macro-recall | 91.2 |
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+ | it_predict/_micro-f1 | 93.11 |
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+ | it_predict/_micro-precision | 98.03 |
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+ | it_predict/_micro-recall | 88.67 |
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+ | it_predict/_steps_per_second | 56.3 |
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+ | it_predict/_weighted-f1 | 93 |
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+ | it_predict/_weighted-precision | 98.13 |
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+ | it_predict/_weighted-recall | 88.67 |
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+ | predict/_CITATION_f1 | 97.36 |
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+ | predict/_CITATION_precision | 98.11 |
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+ | predict/_CITATION_recall | 96.62 |
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+ | predict/_LAW_f1 | 91.68 |
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+ | predict/_LAW_precision | 85.15 |
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+ | predict/_LAW_recall | 99.3 |
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+ | predict/_accuracy_normalized | 98.68 |
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+ | predict/_macro-f1 | 94.56 |
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+ | predict/_macro-precision | 97.96 |
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+ | predict/_macro-recall | 91.7 |
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+ | predict/_micro-f1 | 93.43 |
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+ | predict/_micro-precision | 98.45 |
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+ | predict/_micro-recall | 88.91 |
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+ | predict/_steps_per_second | 55.7 |
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+ | predict/_weighted-f1 | 93.34 |
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+ | predict/_weighted-precision | 98.54 |
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+ | predict/_weighted-recall | 88.91 |
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+ | predict_samples | 28218 |
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+