c-ho / 2026-08-27-crf-classweights-clean

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Total runs: 55
24-hour runs: -824
7-day runs: -811
30-day runs: -72
Model's Last Updated: August 28 2026
token-classification

Introduction of 2026-08-27-crf-classweights-clean

Model Details of 2026-08-27-crf-classweights-clean

2026-08-27-crf-classweights-clean

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 8.6272
  • Precision: 0.7821
  • Recall: 0.8211
  • F1: 0.8011
  • Accuracy: 0.9722
  • Academicdiscipline F1: 0.3810
  • Ambiguouslydefinedconcept F1: 0.7356
  • Discoursephenomenon F1: 0.6549
  • Graphemicphenomenon F1: 0.0
  • Languagerelatedterm F1: 0.8691
  • Languageresourceinformation F1: 0.7868
  • Lexicalphenomenon F1: 0.6759
  • Morphologicalphenomenon F1: 0.8191
  • Morphosyntacticphenomenon F1: 0.8479
  • New Tag F1: 0.8207
  • Otherlinguisticterm F1: 0.7439
  • Phonologicalphenomenon F1: 0.8649
  • Semanticphenomenon F1: 0.7048
  • Syntacticphenomenon F1: 0.7965
  • Topnode Dummy F1: 0.6852
  • Unclassifiedlinguisticconcept F1: 0.8787
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 8
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy Academicdiscipline F1 Ambiguouslydefinedconcept F1 Discoursephenomenon F1 Graphemicphenomenon F1 Languagerelatedterm F1 Languageresourceinformation F1 Lexicalphenomenon F1 Morphologicalphenomenon F1 Morphosyntacticphenomenon F1 New Tag F1 Otherlinguisticterm F1 Phonologicalphenomenon F1 Semanticphenomenon F1 Syntacticphenomenon F1 Topnode Dummy F1 Unclassifiedlinguisticconcept F1
315.3845 1.0 667 14.5431 0.5680 0.5182 0.5420 0.9473 0.0 0.0 0.0 0.0 0.7149 0.2805 0.0176 0.5985 0.6561 0.4946 0.4232 0.7031 0.0 0.5345 0.1853 0.0
60.1323 2.0 1334 8.8849 0.7186 0.7187 0.7187 0.9637 0.5 0.5479 0.5388 0.0 0.7927 0.7110 0.5450 0.7505 0.7886 0.7353 0.6519 0.8232 0.5540 0.6947 0.5443 0.7627
28.8042 3.0 2001 7.9844 0.7165 0.7966 0.7544 0.9663 0.5 0.6 0.5954 0.0 0.8207 0.7217 0.6040 0.7752 0.8127 0.7662 0.6958 0.8428 0.6908 0.7262 0.6268 0.85
19.7129 4.0 2668 7.6316 0.7587 0.7994 0.7785 0.9695 0.4211 0.7314 0.6038 0.0 0.8359 0.756 0.6786 0.8241 0.8171 0.7872 0.7268 0.8528 0.6925 0.7694 0.6604 0.8559
16.1557 5.0 3335 8.0953 0.7406 0.8337 0.7844 0.9691 0.3077 0.7442 0.6696 0.0 0.8418 0.7829 0.6262 0.7988 0.8349 0.8207 0.7372 0.8581 0.7079 0.7754 0.6591 0.8583
10.1011 6.0 4002 8.4333 0.7617 0.8333 0.7959 0.9707 0.3478 0.7619 0.7043 0.0 0.8461 0.7824 0.6582 0.7984 0.8348 0.8173 0.7417 0.8669 0.7135 0.7932 0.6897 0.875
7.3063 7.0 4669 8.6272 0.7821 0.8211 0.8011 0.9722 0.3810 0.7356 0.6549 0.0 0.8691 0.7868 0.6759 0.8191 0.8479 0.8207 0.7439 0.8649 0.7048 0.7965 0.6852 0.8787
6.1858 8.0 5336 9.1583 0.7745 0.8212 0.7972 0.9713 0.3636 0.7640 0.6667 0.0 0.8618 0.7841 0.6771 0.8175 0.8432 0.8139 0.7404 0.8646 0.7028 0.7952 0.6811 0.8729
Framework versions
  • Transformers 4.57.6
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.22.2

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