---
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-conllpp
  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-conllpp

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0443
- Accuracy: 0.9850
- Precision: 0.9304
- Recall: 0.9357
- F1: 0.9330

## 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: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0456        | 1.0   | 3093 | 0.0455          | 0.9804   | 0.9154    | 0.9097 | 0.9126 |
| 0.0441        | 2.0   | 6186 | 0.0444          | 0.9846   | 0.9275    | 0.9316 | 0.9296 |
| 0.0431        | 3.0   | 9279 | 0.0443          | 0.9850   | 0.9304    | 0.9357 | 0.9330 |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1