README.md

metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - conll2003
metrics:
  - f1
model-index:
  - name: bert-base-uncased-for-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: conll2003
          type: conll2003
          config: conll2003
          split: validation
          args: conll2003
        metrics:
          - name: F1
            type: f1
            value: 0.95092693565976

bert-base-uncased-for-ner

This model is a fine-tuned version of bert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0425
• F1: 0.9509

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	F1
0.1058	1.0	586	0.0446	0.9343
0.0282	2.0	1172	0.0405	0.9454
0.0125	3.0	1758	0.0425	0.9509

Framework versions

• Transformers 4.43.3
• Pytorch 2.4.0
• Datasets 2.20.0
• Tokenizers 0.19.1