---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1110_lrate7.5b8
  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_lrate7.5b8

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: 0.6124
- Precisions: 0.8795
- Recall: 0.7898
- F-measure: 0.8228
- Accuracy: 0.9026

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6395        | 1.0   | 471  | 0.4532          | 0.8345     | 0.6789 | 0.6899    | 0.8619   |
| 0.3636        | 2.0   | 942  | 0.3956          | 0.8284     | 0.7491 | 0.7766    | 0.8853   |
| 0.2471        | 3.0   | 1413 | 0.5037          | 0.8053     | 0.6950 | 0.7258    | 0.8821   |
| 0.1785        | 4.0   | 1884 | 0.5098          | 0.8444     | 0.7522 | 0.7755    | 0.8936   |
| 0.1279        | 5.0   | 2355 | 0.5574          | 0.8751     | 0.7735 | 0.8077    | 0.8973   |
| 0.097         | 6.0   | 2826 | 0.6124          | 0.8795     | 0.7898 | 0.8228    | 0.9026   |
| 0.071         | 7.0   | 3297 | 0.5377          | 0.8621     | 0.7836 | 0.8157    | 0.9044   |
| 0.0494        | 8.0   | 3768 | 0.5842          | 0.8705     | 0.7725 | 0.8109    | 0.9029   |
| 0.0344        | 9.0   | 4239 | 0.6835          | 0.8705     | 0.7506 | 0.7912    | 0.9010   |
| 0.0276        | 10.0  | 4710 | 0.6916          | 0.8226     | 0.7864 | 0.7999    | 0.9048   |
| 0.0174        | 11.0  | 5181 | 0.7412          | 0.8646     | 0.7491 | 0.7905    | 0.8994   |
| 0.0112        | 12.0  | 5652 | 0.7701          | 0.8258     | 0.7647 | 0.7866    | 0.9018   |
| 0.0084        | 13.0  | 6123 | 0.7811          | 0.8331     | 0.7593 | 0.7899    | 0.9058   |
| 0.0063        | 14.0  | 6594 | 0.7682          | 0.8636     | 0.7763 | 0.8112    | 0.9064   |


### Framework versions

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