---
library_name: transformers
license: apache-2.0
base_model: huggingface-course/bert-finetuned-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_model_output
  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_output

This model is a fine-tuned version of [huggingface-course/bert-finetuned-ner](https://huggingface.co/huggingface-course/bert-finetuned-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2567
- Precision: 0.6421
- Recall: 0.6747
- F1: 0.6580
- Accuracy: 0.9242

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4135        | 1.0   | 1756 | 0.3290          | 0.5395    | 0.5106 | 0.5246 | 0.8946   |
| 0.2314        | 2.0   | 3512 | 0.2702          | 0.6515    | 0.6254 | 0.6382 | 0.9213   |
| 0.1599        | 3.0   | 5268 | 0.2567          | 0.6421    | 0.6747 | 0.6580 | 0.9242   |


### Framework versions

- Transformers 5.14.1
- Pytorch 2.13.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2