bert-base-cased-ner-jnlpba-strong-labelled

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

• eval_loss: 1.7948
• eval_accuracy: 0.1970
• eval_runtime: 49.3802
• eval_samples_per_second: 156.217
• eval_steps_per_second: 9.781
• 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Framework versions

• Transformers 4.25.1
• Pytorch 1.12.1+cu113
• Datasets 2.8.0
• Tokenizers 0.13.2