---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: multibertfinetuned1107
  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. -->

# multibertfinetuned1107

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: 0.5977
- Precision: 0.6463
- Recall: 0.6078
- F1: 0.6264
- Accuracy: 0.8835

## 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: 5e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 145  | 0.6113          | 0.6550    | 0.5854 | 0.6182 | 0.8735   |
| No log        | 2.0   | 290  | 0.6457          | 0.6270    | 0.5659 | 0.5949 | 0.8705   |
| No log        | 3.0   | 435  | 0.5977          | 0.6463    | 0.6078 | 0.6264 | 0.8835   |
| 0.1409        | 4.0   | 580  | 0.6095          | 0.6752    | 0.6449 | 0.6597 | 0.8865   |
| 0.1409        | 5.0   | 725  | 0.6566          | 0.6680    | 0.6380 | 0.6527 | 0.8851   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3