---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ncbi_disease
model-index:
- name: ner_model
  results: []
---

<!-- 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. -->

# ner_model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.0047
- eval_model_preparation_time: 0.0051
- eval_precision: 0.0553
- eval_recall: 0.1916
- eval_f1: 0.0858
- eval_accuracy: 0.6607
- eval_runtime: 4.1414
- eval_samples_per_second: 227.217
- eval_steps_per_second: 28.493
- 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: 8
- eval_batch_size: 8
- 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