distilbert-base-uncased-finetuned-ner

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distilbert-base-uncased-finetuned-ner

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

• Loss: 0.0686
• Precision: 0.9022
• Recall: 0.9216
• F1: 0.9118
• Accuracy: 0.9807

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.57.1
• Pytorch 2.9.0+cpu
• Datasets 4.4.1
• Tokenizers 0.22.1