distilbert-base-uncased-finetuned-ner-nlp

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distilbert-base-uncased-finetuned-ner-nlp

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0812
• Precision: 0.8835
• Recall: 0.9039
• F1: 0.8936
• Accuracy: 0.9804

Model description

Essential info about tagged entities

• geo: Geographical Entity
• gpe: Geopolitical Entity
• tim: Time Indicator

Label description

• Label 0: 'B-geo',
• Label 1: 'B-gpe',
• Label 2: 'B-tim',
• Label 3: 'I-geo',
• Label 4: 'I-gpe',
• Label 5: 'I-tim',
• Label 6: 'O'

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Framework versions

• Transformers 4.24.0
• Pytorch 1.12.1+cu113
• Datasets 2.7.0
• Tokenizers 0.13.2