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drbert-7gb-finedtuned-ner

Token Classification
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drbert-7gb-finedtuned-ner

This model is a fine-tuned version of Dr-BERT/DrBERT-7GB on the quaero dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2330
  • Precision: 0.5055
  • Recall: 0.5696
  • F1: 0.5357
  • Accuracy: 0.8004

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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
No log 1.0 105 0.7430 0.4129 0.4775 0.4428 0.7671
No log 2.0 210 0.6968 0.4888 0.5042 0.4964 0.7888
No log 3.0 315 0.8218 0.5059 0.5323 0.5188 0.7952
No log 4.0 420 0.9307 0.4869 0.5563 0.5193 0.7913
0.4134 5.0 525 0.9970 0.4688 0.5581 0.5095 0.7870
0.4134 6.0 630 1.0503 0.4992 0.5541 0.5252 0.7930
0.4134 7.0 735 1.1364 0.5034 0.5607 0.5305 0.7994
0.4134 8.0 840 1.1994 0.4865 0.5701 0.5250 0.7937
0.4134 9.0 945 1.2287 0.4948 0.5683 0.5290 0.7982
0.028 10.0 1050 1.2330 0.5055 0.5696 0.5357 0.8004

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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Evaluation results

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