---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-bert-base-multilingual-uncased-NED_latest
  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. -->

# fine-tuned-bert-base-multilingual-uncased-NED_latest

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1376
- Accuracy: 0.9687
- Precision: 0.9761
- Recall: 0.9764
- F1: 0.9762

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.157         | 1.0   | 56232  | 0.1271          | 0.9658   | 0.9740    | 0.9741 | 0.9740 |
| 0.144         | 2.0   | 112464 | 0.1549          | 0.9665   | 0.9693    | 0.9802 | 0.9747 |
| 0.1439        | 3.0   | 168696 | 0.1600          | 0.9660   | 0.9701    | 0.9786 | 0.9743 |
| 0.1267        | 4.0   | 224928 | 0.1376          | 0.9687   | 0.9761    | 0.9764 | 0.9762 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1