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

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1307
- Precision: 0.9077
- Recall: 0.9222
- F1: 0.9149
- Accuracy: 0.9833

## 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: 3e-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: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0429        | 1.0   | 878  | 0.0399          | 0.9270    | 0.9368 | 0.9319 | 0.9890   |
| 0.0186        | 2.0   | 1756 | 0.0402          | 0.9458    | 0.9501 | 0.9480 | 0.9910   |
| 0.0094        | 3.0   | 2634 | 0.0386          | 0.9500    | 0.9537 | 0.9518 | 0.9916   |
| 0.0036        | 4.0   | 3512 | 0.0392          | 0.9491    | 0.9549 | 0.9520 | 0.9917   |
| 0.0018        | 5.0   | 4390 | 0.0393          | 0.9503    | 0.9565 | 0.9534 | 0.9918   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2