---
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-model
  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

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: 0.1297
- Precision: 0.8229
- Recall: 0.8866
- F1: 0.8535
- Accuracy: 0.9667

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1752        | 1.0   | 2489  | 0.1261          | 0.7649    | 0.8137 | 0.7885 | 0.9549   |
| 0.1076        | 2.0   | 4978  | 0.1184          | 0.7881    | 0.8592 | 0.8221 | 0.9611   |
| 0.074         | 3.0   | 7467  | 0.1137          | 0.7985    | 0.8802 | 0.8374 | 0.9634   |
| 0.0634        | 4.0   | 9956  | 0.1239          | 0.8125    | 0.8927 | 0.8507 | 0.9651   |
| 0.0387        | 5.0   | 12445 | 0.1297          | 0.8229    | 0.8866 | 0.8535 | 0.9667   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1