README.md

metadata

license: apache-2.0
base_model: dslim/distilbert-NER
tags:
  - generated_from_trainer
datasets:
  - conll2012_ontonotesv5
metrics:
  - f1
model-index:
  - name: distilbert-NER-finetuned-bert-tiny
    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: F1
            type: f1
            value: 0.4683072334079046

distilbert-NER-finetuned-bert-tiny

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: 0.5602
• F1: 0.4683

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
1.0495	1.0	81	0.7833	0.3529
0.6421	2.0	162	0.6088	0.4570
0.5065	3.0	243	0.5602	0.4683

Framework versions

• Transformers 4.42.4
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1