distilbert-base-uncased-finetuned-ner

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

distilbert-base-uncased-finetuned-ner

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0788
• eval_model_preparation_time: 0.0015
• eval_precision: 0.8041
• eval_recall: 0.8533
• eval_f1: 0.8280
• eval_accuracy: 0.9795
• eval_runtime: 3.3268
• eval_samples_per_second: 277.743
• eval_steps_per_second: 17.434
• step: 0

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1