metadata

license: apache-2.0
base_model: dslim/distilbert-NER
tags:
  - generated_from_trainer
datasets:
  - conll2012_ontonotesv5
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-NER-finetuned
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: conll2012_ontonotesv5
          type: conll2012_ontonotesv5
          config: english_v4
          split: validation
          args: english_v4
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.867816091954023
          - name: F1
            type: f1
            value: 0.4862665310274669

distilbert-NER-finetuned

This model is a fine-tuned version of dslim/distilbert-NER on the conll2012_ontonotesv5 dataset. It achieves the following results on the evaluation set:

Loss: 0.5043
Accuracy: 0.8678
F1: 0.4863

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: 24
eval_batch_size: 24
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	Accuracy	F1
0.9019	1.0	61	0.6286	0.8406	0.4223
0.5594	2.0	122	0.5302	0.8605	0.4567
0.4537	3.0	183	0.5043	0.8678	0.4863

Framework versions

Transformers 4.42.4
Pytorch 2.4.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1