---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_1210seed7
  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_1210seed7

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: 0.5019
- Precisions: 0.8874
- Recall: 0.7790
- F-measure: 0.8105
- Accuracy: 0.9107

## 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: 7
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6032        | 1.0   | 236  | 0.4733          | 0.8608     | 0.6507 | 0.6853    | 0.8645   |
| 0.3527        | 2.0   | 472  | 0.3790          | 0.8098     | 0.7259 | 0.7383    | 0.8826   |
| 0.2198        | 3.0   | 708  | 0.4191          | 0.8209     | 0.7632 | 0.7816    | 0.8936   |
| 0.1359        | 4.0   | 944  | 0.4433          | 0.8430     | 0.7344 | 0.7590    | 0.8924   |
| 0.0862        | 5.0   | 1180 | 0.5207          | 0.8067     | 0.7697 | 0.7838    | 0.8947   |
| 0.0637        | 6.0   | 1416 | 0.5019          | 0.8874     | 0.7790 | 0.8105    | 0.9107   |
| 0.0454        | 7.0   | 1652 | 0.5048          | 0.8049     | 0.8135 | 0.8070    | 0.9058   |
| 0.0318        | 8.0   | 1888 | 0.5969          | 0.8135     | 0.7710 | 0.7845    | 0.9003   |
| 0.024         | 9.0   | 2124 | 0.6388          | 0.8295     | 0.7999 | 0.8057    | 0.9048   |
| 0.0138        | 10.0  | 2360 | 0.6448          | 0.8304     | 0.7727 | 0.7949    | 0.9033   |
| 0.0084        | 11.0  | 2596 | 0.6589          | 0.8216     | 0.7756 | 0.7936    | 0.9017   |
| 0.0091        | 12.0  | 2832 | 0.6471          | 0.8340     | 0.7683 | 0.7952    | 0.9045   |
| 0.005         | 13.0  | 3068 | 0.6817          | 0.8600     | 0.7662 | 0.8034    | 0.9073   |
| 0.0045        | 14.0  | 3304 | 0.6774          | 0.8397     | 0.7680 | 0.7976    | 0.9077   |


### Framework versions

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