---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_1210seed85
  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. -->

# multibert_1210seed85

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: 0.4043
- Precisions: 0.8689
- Recall: 0.8339
- F-measure: 0.8498
- Accuracy: 0.9067

## 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: 85
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.5968        | 1.0   | 236  | 0.4307          | 0.8843     | 0.6749 | 0.7165    | 0.8690   |
| 0.3238        | 2.0   | 472  | 0.3849          | 0.8827     | 0.7215 | 0.7489    | 0.8916   |
| 0.2021        | 3.0   | 708  | 0.4067          | 0.8540     | 0.7640 | 0.7969    | 0.8983   |
| 0.1335        | 4.0   | 944  | 0.3857          | 0.8227     | 0.8002 | 0.8071    | 0.8983   |
| 0.0886        | 5.0   | 1180 | 0.4043          | 0.8689     | 0.8339 | 0.8498    | 0.9067   |
| 0.0654        | 6.0   | 1416 | 0.4734          | 0.8847     | 0.8016 | 0.8359    | 0.9089   |
| 0.0451        | 7.0   | 1652 | 0.5312          | 0.8215     | 0.7826 | 0.7996    | 0.8980   |
| 0.031         | 8.0   | 1888 | 0.5520          | 0.8730     | 0.7873 | 0.8222    | 0.9074   |
| 0.0248        | 9.0   | 2124 | 0.4954          | 0.8896     | 0.8145 | 0.8454    | 0.9149   |
| 0.0149        | 10.0  | 2360 | 0.5595          | 0.8717     | 0.8101 | 0.8354    | 0.9104   |
| 0.0086        | 11.0  | 2596 | 0.5703          | 0.8814     | 0.8051 | 0.8348    | 0.9112   |
| 0.0061        | 12.0  | 2832 | 0.5855          | 0.8655     | 0.8138 | 0.8356    | 0.9103   |
| 0.006         | 13.0  | 3068 | 0.6068          | 0.8578     | 0.8137 | 0.8329    | 0.9105   |
| 0.0039        | 14.0  | 3304 | 0.6147          | 0.8656     | 0.8129 | 0.8356    | 0.9112   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1