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

# uner-bert-ner

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: 0.1354
- Precision: 0.8267
- Recall: 0.8707
- F1: 0.8481
- Accuracy: 0.9640

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 144  | 0.1496          | 0.7687    | 0.7971 | 0.7826 | 0.9533   |
| No log        | 2.0   | 288  | 0.1429          | 0.7719    | 0.8584 | 0.8129 | 0.9573   |
| No log        | 3.0   | 432  | 0.1267          | 0.8014    | 0.8682 | 0.8335 | 0.9629   |
| 0.1628        | 4.0   | 576  | 0.1316          | 0.8206    | 0.8723 | 0.8457 | 0.9644   |
| 0.1628        | 5.0   | 720  | 0.1354          | 0.8267    | 0.8707 | 0.8481 | 0.9640   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3