---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: ner
  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

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|
| 0.1717        | 1.0   | 125  | 0.0026          | 1.0       | 1.0    | 1.0 |
| 0.0022        | 2.0   | 250  | 0.0007          | 1.0       | 1.0    | 1.0 |
| 0.0014        | 3.0   | 375  | 0.0004          | 1.0       | 1.0    | 1.0 |
| 0.0010        | 4.0   | 500  | 0.0004          | 1.0       | 1.0    | 1.0 |
| 0.0008        | 5.0   | 625  | 0.0003          | 1.0       | 1.0    | 1.0 |


### Framework versions

- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2