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

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Precision: 1.0
- Recall: 0.9993
- F1: 0.9997
- Accuracy: 1.0000

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0005        | 0.1   | 250  | 0.0047          | 0.9998    | 0.9861 | 0.9929 | 0.9994   |
| 0.009         | 0.2   | 500  | 0.0041          | 0.9961    | 0.9864 | 0.9912 | 0.9994   |
| 0.0004        | 0.3   | 750  | 0.0024          | 0.9977    | 0.9895 | 0.9936 | 0.9995   |
| 0.0001        | 0.4   | 1000 | 0.0010          | 0.9984    | 0.9975 | 0.9980 | 0.9999   |
| 0.0001        | 0.51  | 1250 | 0.0008          | 1.0       | 0.9975 | 0.9987 | 0.9999   |
| 0.0001        | 0.61  | 1500 | 0.0005          | 1.0       | 0.9975 | 0.9987 | 0.9999   |
| 0.0003        | 0.71  | 1750 | 0.0003          | 1.0       | 0.9991 | 0.9995 | 1.0000   |
| 0.0001        | 0.81  | 2000 | 0.0002          | 1.0       | 0.9993 | 0.9997 | 1.0000   |
| 0.0           | 0.91  | 2250 | 0.0002          | 1.0       | 0.9993 | 0.9997 | 1.0000   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0