Edit model card

roberta-base-bne-capitel-ner

This model is a fine-tuned version of BSC-LT/roberta-base-bne-capitel-ner on the conll2002 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1137
  • Precision: 0.8638
  • Recall: 0.8814
  • F1: 0.8725
  • Accuracy: 0.9780

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: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0041 1.0 1041 0.1137 0.8638 0.8814 0.8725 0.9780
0.004 2.0 2082 0.1137 0.8638 0.8814 0.8725 0.9780
0.0039 3.0 3123 0.1137 0.8638 0.8814 0.8725 0.9780
0.003 4.0 4164 0.1137 0.8638 0.8814 0.8725 0.9780
0.0032 5.0 5205 0.1137 0.8638 0.8814 0.8725 0.9780

Framework versions

  • Transformers 4.30.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3
Downloads last month
72
Safetensors
Model size
124M params
Tensor type
F32
·

Dataset used to train raulgdp/roberta-base-bne-capitel-ner

Evaluation results