File size: 1,627 Bytes
58740ff |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
---
datasets:
- LawInformedAI/claudette_tos
language:
- en
base_model:
- nlpaueb/legal-bert-base-uncased
pipeline_tag: text-classification
---
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)
{
"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,
"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,
"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,
"eval_steps_per_second": 0.579,
"step": 261
}, |