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--- |
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datasets: |
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- LawInformedAI/claudette_tos |
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language: |
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- en |
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base_model: |
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- nlpaueb/legal-bert-base-uncased |
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pipeline_tag: text-classification |
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--- |
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|
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LegalBert trained as sequence classifier for multilabel classification on 8 unfairness labels + FAIR label, multilabel (a ToS can have multiple labels, trying to guess them all) |
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|
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{ |
|
"epoch": 0.999043062200957, |
|
"eval_A_f1": 0.0, |
|
"eval_A_precision": 0.0, |
|
"eval_A_recall": 0.0, |
|
"eval_CH_f1": 0.0, |
|
"eval_CH_precision": 0.0, |
|
"eval_CH_recall": 0.0, |
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"eval_CR_f1": 0.0, |
|
"eval_CR_precision": 0.0, |
|
"eval_CR_recall": 0.0, |
|
"eval_FAIR_f1": 0.9544351203273459, |
|
"eval_FAIR_precision": 0.9774147727272727, |
|
"eval_FAIR_recall": 0.9325111803767449, |
|
"eval_J_f1": 0.0, |
|
"eval_J_precision": 0.0, |
|
"eval_J_recall": 0.0, |
|
"eval_LAW_f1": 0.0, |
|
"eval_LAW_precision": 0.0, |
|
"eval_LAW_recall": 0.0, |
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"eval_LTD_f1": 0.6153846153846154, |
|
"eval_LTD_precision": 0.7472527472527473, |
|
"eval_LTD_recall": 0.5230769230769231, |
|
"eval_TER_f1": 0.0, |
|
"eval_TER_precision": 0.0, |
|
"eval_TER_recall": 0.0, |
|
"eval_USE_f1": 0.017241379310344827, |
|
"eval_USE_precision": 1.0, |
|
"eval_USE_recall": 0.008695652173913044, |
|
"eval_accuracy": 0.8484116439183477, |
|
"eval_f1_macro": 0.17634012389136736, |
|
"eval_loss": 0.06019286438822746, |
|
"eval_precision_macro": 0.3027408355533356, |
|
"eval_recall_macro": 0.1626981950697312, |
|
"eval_runtime": 894.9212, |
|
"eval_samples_per_second": 9.251, |
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"eval_steps_per_second": 0.579, |
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"step": 261 |
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}, |
