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

• eval_loss: 0.0841
• eval_precision: 0.8833
• eval_recall: 0.9042
• eval_f1: 0.8936
• eval_accuracy: 0.9762
• eval_runtime: 115.4849
• eval_samples_per_second: 28.142
• eval_steps_per_second: 1.766
• epoch: 0.57
• step: 500

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Framework versions

• Transformers 4.37.1
• Pytorch 2.0.0+cpu
• Datasets 2.16.1
• Tokenizers 0.15.1