bert-finetuned-ner

This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.1061
• eval_precision: 0.8323
• eval_recall: 0.9068
• eval_f1: 0.8679
• eval_accuracy: 0.9736
• eval_runtime: 8.0223
• eval_samples_per_second: 405.122
• eval_steps_per_second: 25.429
• epoch: 1.0
• step: 625

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 4.50.0
• Pytorch 2.11.0+cu128
• Datasets 3.4.1
• Tokenizers 0.21.4