---
license: apache-2.0
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: 0.5260
- Precision: 0.5933
- Recall: 0.4839
- F1: 0.5330
- Accuracy: 0.8502

## 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  | 0.5260          | 0.5933    | 0.4839 | 0.5330 | 0.8502   |
| No log        | 2.0   | 290  | 0.5357          | 0.6099    | 0.5415 | 0.5736 | 0.8604   |
| No log        | 3.0   | 435  | 0.5476          | 0.6279    | 0.5795 | 0.6027 | 0.8715   |
| 0.365         | 4.0   | 580  | 0.5861          | 0.6454    | 0.6107 | 0.6276 | 0.8827   |
| 0.365         | 5.0   | 725  | 0.6235          | 0.6543    | 0.6185 | 0.6359 | 0.8804   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3