dmargutierrez / distilbert-base-multilingual-cased-mapa_coarse-ner

huggingface.co
Total runs: 5.5K
24-hour runs: 14
7-day runs: 1.0K
30-day runs: 1.5K
Model's Last Updated: March 17 2023
token-classification

Introduction of distilbert-base-multilingual-cased-mapa_coarse-ner

Model Details of distilbert-base-multilingual-cased-mapa_coarse-ner

distilbert-base-multilingual-cased-mapa_coarse-ner

This model is a fine-tuned version of distilbert-base-multilingual-cased on the lextreme dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0882
  • Precision: 0.7191
  • Recall: 0.6453
  • F1: 0.6802
  • Accuracy: 0.9879
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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0248 1.0 1739 0.0528 0.7451 0.5805 0.6525 0.9871
0.0181 2.0 3478 0.0595 0.7369 0.5749 0.6459 0.9875
0.0121 3.0 5217 0.0499 0.7404 0.6280 0.6796 0.9879
0.0088 4.0 6956 0.0634 0.6912 0.6334 0.6610 0.9875
0.0072 5.0 8695 0.0625 0.7109 0.6478 0.6779 0.9880
0.0052 6.0 10434 0.0702 0.7098 0.6518 0.6796 0.9878
0.0041 7.0 12173 0.0733 0.7176 0.6429 0.6782 0.9878
0.0026 8.0 13912 0.0779 0.7198 0.6540 0.6853 0.9879
0.0019 9.0 15651 0.0875 0.7181 0.6419 0.6779 0.9877
0.0018 10.0 17390 0.0882 0.7191 0.6453 0.6802 0.9879
Framework versions
  • Transformers 4.26.0
  • Pytorch 1.13.1+cu117
  • Datasets 2.9.0
  • Tokenizers 0.13.2

Runs of dmargutierrez distilbert-base-multilingual-cased-mapa_coarse-ner on huggingface.co

5.5K
Total runs
14
24-hour runs
359
3-day runs
1.0K
7-day runs
1.5K
30-day runs

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