---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: MBERTdataaugmentation1511
  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. -->

# MBERTdataaugmentation1511

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: 0.4799
- Precisions: 0.8775
- Recall: 0.8066
- F-measure: 0.8358
- Accuracy: 0.9364

## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 34
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4277        | 1.0   | 284  | 0.2782          | 0.7721     | 0.7565 | 0.7579    | 0.9183   |
| 0.1776        | 2.0   | 568  | 0.2903          | 0.8401     | 0.7736 | 0.8007    | 0.9265   |
| 0.0953        | 3.0   | 852  | 0.3116          | 0.8565     | 0.7792 | 0.8124    | 0.9337   |
| 0.067         | 4.0   | 1136 | 0.3747          | 0.8019     | 0.7974 | 0.7931    | 0.9253   |
| 0.0424        | 5.0   | 1420 | 0.3834          | 0.8297     | 0.7751 | 0.7971    | 0.9306   |
| 0.0288        | 6.0   | 1704 | 0.4208          | 0.8641     | 0.7981 | 0.8245    | 0.9313   |
| 0.0187        | 7.0   | 1988 | 0.4472          | 0.8374     | 0.8033 | 0.8148    | 0.9323   |
| 0.0105        | 8.0   | 2272 | 0.4297          | 0.8652     | 0.7903 | 0.8181    | 0.9332   |
| 0.0085        | 9.0   | 2556 | 0.4425          | 0.8567     | 0.8019 | 0.8250    | 0.9344   |
| 0.0044        | 10.0  | 2840 | 0.4744          | 0.8493     | 0.8075 | 0.8256    | 0.9347   |
| 0.004         | 11.0  | 3124 | 0.4967          | 0.8581     | 0.8017 | 0.8251    | 0.9361   |
| 0.003         | 12.0  | 3408 | 0.4799          | 0.8775     | 0.8066 | 0.8358    | 0.9364   |
| 0.0015        | 13.0  | 3692 | 0.5093          | 0.8803     | 0.7943 | 0.8294    | 0.9356   |
| 0.0014        | 14.0  | 3976 | 0.4985          | 0.8762     | 0.7964 | 0.8281    | 0.9359   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1