metadata

license: mit
base_model: FacebookAI/roberta-base
tags:
  - generated_from_trainer
datasets:
  - conll2003
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: RoBerta-finetuned-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: conll2003
          type: conll2003
          config: conll2003
          split: validation
          args: conll2003
        metrics:
          - name: Precision
            type: precision
            value: 0.9502164502164502
          - name: Recall
            type: recall
            value: 0.9604510265903736
          - name: F1
            type: f1
            value: 0.9553063274188148
          - name: Accuracy
            type: accuracy
            value: 0.9898284802552852

RoBerta-finetuned-ner

This Name Entity Recognition model is a fine-tuned version of FacebookAI/roberta-base on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0605
Precision: 0.9502
Recall: 0.9605
F1: 0.9553
Accuracy: 0.9898

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0248	1.0	1756	0.0636	0.9474	0.9547	0.9510	0.9885
0.014	2.0	3512	0.0734	0.9483	0.9578	0.9530	0.9886
0.0124	3.0	5268	0.0605	0.9502	0.9605	0.9553	0.9898

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1