---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- f1
- precision
- recall
model-index:
- name: bert-base-cased-conll2003-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: validation
      args: conll2003
    metrics:
    - name: F1
      type: f1
      value: 0.911552663970459
    - name: Precision
      type: precision
      value: 0.9053440447083478
    - name: Recall
      type: recall
      value: 0.9178470254957507
---

<!-- 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. -->

# bert-base-cased-conll2003-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1194
- F1: 0.9116
- Precision: 0.9053
- Recall: 0.9178

## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.1659        | 1.0   | 878  | 0.0414          | 0.9342 | 0.9314    | 0.9371 |
| 0.0279        | 2.0   | 1756 | 0.0383          | 0.9480 | 0.9463    | 0.9497 |
| 0.0145        | 3.0   | 2634 | 0.0374          | 0.9518 | 0.9497    | 0.9539 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 2.21.0
- Tokenizers 0.22.2