---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mbert-finetuned-azerbaijani-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: wikiann
      type: wikiann
      args: az
    metrics:
    - name: Precision
      type: precision
      value: 0.8898541731306236
    - name: Recall
      type: recall
      value: 0.915416533673795
    - name: F1
      type: f1
      value: 0.9024543738200126
    - name: Accuracy
      type: accuracy
      value: 0.966948310139165
---

<!-- 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. -->

# mbert-finetuned-azerbaijani-ner

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1385
- Precision: 0.8899
- Recall: 0.9154
- F1: 0.9025
- Accuracy: 0.9669

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2928        | 1.0   | 625  | 0.1415          | 0.8584    | 0.8918 | 0.8748 | 0.9595   |
| 0.1254        | 2.0   | 1250 | 0.1335          | 0.8875    | 0.9119 | 0.8996 | 0.9637   |
| 0.077         | 3.0   | 1875 | 0.1385          | 0.8899    | 0.9154 | 0.9025 | 0.9669   |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6