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

# bert-finetuned-ner

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: 0.0616
- Precision: 0.9319
- Recall: 0.9488
- F1: 0.9403
- Accuracy: 0.9856

## 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_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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.1503 | 264  | 0.1354          | 0.7782    | 0.8544 | 0.8145 | 0.9625   |
| 0.2679        | 0.3007 | 528  | 0.0971          | 0.8526    | 0.9005 | 0.8759 | 0.9736   |
| 0.2679        | 0.4510 | 792  | 0.0887          | 0.8900    | 0.9222 | 0.9059 | 0.9781   |
| 0.105         | 0.6014 | 1056 | 0.0809          | 0.9094    | 0.9278 | 0.9185 | 0.9804   |
| 0.105         | 0.7517 | 1320 | 0.0714          | 0.9137    | 0.9342 | 0.9239 | 0.9812   |
| 0.0748        | 0.9021 | 1584 | 0.0645          | 0.9181    | 0.9377 | 0.9278 | 0.9836   |
| 0.0748        | 1.0524 | 1848 | 0.0735          | 0.9173    | 0.9392 | 0.9282 | 0.9825   |
| 0.0634        | 1.2027 | 2112 | 0.0692          | 0.9129    | 0.9389 | 0.9257 | 0.9826   |
| 0.0634        | 1.3531 | 2376 | 0.0691          | 0.9297    | 0.9478 | 0.9387 | 0.9851   |
| 0.0428        | 1.5034 | 2640 | 0.0660          | 0.9229    | 0.9448 | 0.9337 | 0.9844   |
| 0.0428        | 1.6538 | 2904 | 0.0602          | 0.9292    | 0.9450 | 0.9370 | 0.9855   |
| 0.0448        | 1.8041 | 3168 | 0.0603          | 0.9165    | 0.9461 | 0.9311 | 0.9844   |
| 0.0448        | 1.9544 | 3432 | 0.0636          | 0.9311    | 0.9458 | 0.9384 | 0.9848   |
| 0.0364        | 2.1048 | 3696 | 0.0686          | 0.9305    | 0.9461 | 0.9383 | 0.9853   |
| 0.0364        | 2.2551 | 3960 | 0.0632          | 0.9338    | 0.9497 | 0.9417 | 0.9857   |
| 0.0211        | 2.4055 | 4224 | 0.0644          | 0.9284    | 0.9450 | 0.9366 | 0.9845   |
| 0.0211        | 2.5558 | 4488 | 0.0628          | 0.9331    | 0.9458 | 0.9394 | 0.9846   |
| 0.0209        | 2.7062 | 4752 | 0.0602          | 0.9287    | 0.9473 | 0.9379 | 0.9853   |
| 0.0221        | 2.8565 | 5016 | 0.0616          | 0.9319    | 0.9488 | 0.9403 | 0.9856   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1