---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1110_lrate7.5b4
  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. -->

# multibert1110_lrate7.5b4

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: 0.7163
- Precisions: 0.8864
- Recall: 0.8013
- F-measure: 0.8374
- Accuracy: 0.9059

## 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: 4
- eval_batch_size: 4
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.7304        | 1.0   | 942   | 0.4905          | 0.8049     | 0.6436 | 0.6549    | 0.8554   |
| 0.4336        | 2.0   | 1884  | 0.6035          | 0.8585     | 0.6334 | 0.6863    | 0.8477   |
| 0.3238        | 3.0   | 2826  | 0.5094          | 0.8668     | 0.7014 | 0.7232    | 0.8882   |
| 0.249         | 4.0   | 3768  | 0.5951          | 0.8798     | 0.7110 | 0.7609    | 0.8770   |
| 0.191         | 5.0   | 4710  | 0.4988          | 0.8304     | 0.7761 | 0.7816    | 0.8975   |
| 0.1513        | 6.0   | 5652  | 0.5998          | 0.8351     | 0.7917 | 0.8062    | 0.8962   |
| 0.1088        | 7.0   | 6594  | 0.5874          | 0.8427     | 0.7953 | 0.8158    | 0.9003   |
| 0.0914        | 8.0   | 7536  | 0.5529          | 0.8580     | 0.7885 | 0.8087    | 0.9069   |
| 0.0682        | 9.0   | 8478  | 0.6882          | 0.8371     | 0.7773 | 0.8024    | 0.8958   |
| 0.0487        | 10.0  | 9420  | 0.7163          | 0.8864     | 0.8013 | 0.8374    | 0.9059   |
| 0.0319        | 11.0  | 10362 | 0.7020          | 0.8724     | 0.7867 | 0.8235    | 0.9007   |
| 0.0305        | 12.0  | 11304 | 0.6886          | 0.8689     | 0.8002 | 0.8311    | 0.9079   |
| 0.0184        | 13.0  | 12246 | 0.6994          | 0.8680     | 0.8089 | 0.8357    | 0.9085   |
| 0.0138        | 14.0  | 13188 | 0.7183          | 0.8677     | 0.8105 | 0.8362    | 0.9093   |


### Framework versions

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