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

# bert-base-multilingual-cased-finetuned-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: 0.2939
- Accuracy: 0.4501
- Precision: 0.5440
- Recall: 0.6659
- F1: 0.4954

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 50   | 0.5390          | 0.3903   | 0.5183    | 0.4448 | 0.3118 |
| No log        | 2.0   | 100  | 0.4150          | 0.4152   | 0.5575    | 0.5062 | 0.3632 |
| No log        | 3.0   | 150  | 0.3530          | 0.4289   | 0.5842    | 0.5557 | 0.3945 |
| No log        | 4.0   | 200  | 0.3272          | 0.4348   | 0.5319    | 0.5761 | 0.4145 |
| No log        | 5.0   | 250  | 0.3047          | 0.4401   | 0.5175    | 0.6018 | 0.4284 |
| No log        | 6.0   | 300  | 0.2964          | 0.4422   | 0.5224    | 0.6224 | 0.4600 |
| No log        | 7.0   | 350  | 0.2927          | 0.4445   | 0.5391    | 0.6302 | 0.4691 |
| No log        | 8.0   | 400  | 0.2896          | 0.4457   | 0.5295    | 0.6335 | 0.4668 |
| No log        | 9.0   | 450  | 0.2810          | 0.4482   | 0.5360    | 0.6535 | 0.4846 |
| 0.324         | 10.0  | 500  | 0.2852          | 0.4486   | 0.5383    | 0.6554 | 0.4847 |
| 0.324         | 11.0  | 550  | 0.2949          | 0.4482   | 0.5372    | 0.6560 | 0.4858 |
| 0.324         | 12.0  | 600  | 0.2938          | 0.4494   | 0.5437    | 0.6603 | 0.4917 |
| 0.324         | 13.0  | 650  | 0.2906          | 0.4503   | 0.5437    | 0.6664 | 0.4952 |
| 0.324         | 14.0  | 700  | 0.2963          | 0.4499   | 0.5466    | 0.6641 | 0.4957 |
| 0.324         | 15.0  | 750  | 0.2939          | 0.4501   | 0.5440    | 0.6659 | 0.4954 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1