---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1110_lrate5b16
  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_lrate5b16

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: 0.5618
- Precisions: 0.8632
- Recall: 0.8248
- F-measure: 0.8416
- Accuracy: 0.9160

## 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: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.5858        | 1.0   | 236  | 0.3670          | 0.8368     | 0.6841 | 0.7038    | 0.8774   |
| 0.302         | 2.0   | 472  | 0.3603          | 0.8064     | 0.7589 | 0.7780    | 0.8931   |
| 0.1746        | 3.0   | 708  | 0.3442          | 0.8616     | 0.7693 | 0.7773    | 0.9026   |
| 0.118         | 4.0   | 944  | 0.4355          | 0.8683     | 0.7908 | 0.8197    | 0.9039   |
| 0.0822        | 5.0   | 1180 | 0.4320          | 0.8775     | 0.8042 | 0.8343    | 0.9094   |
| 0.0597        | 6.0   | 1416 | 0.4654          | 0.8722     | 0.8075 | 0.8298    | 0.9089   |
| 0.0363        | 7.0   | 1652 | 0.5211          | 0.8768     | 0.7803 | 0.8192    | 0.9054   |
| 0.0258        | 8.0   | 1888 | 0.4996          | 0.8631     | 0.8111 | 0.8306    | 0.9133   |
| 0.0165        | 9.0   | 2124 | 0.6172          | 0.8984     | 0.7691 | 0.8095    | 0.9073   |
| 0.0135        | 10.0  | 2360 | 0.5919          | 0.8912     | 0.7948 | 0.8312    | 0.9130   |
| 0.0111        | 11.0  | 2596 | 0.5726          | 0.8704     | 0.8003 | 0.8280    | 0.9143   |
| 0.0079        | 12.0  | 2832 | 0.5618          | 0.8632     | 0.8248 | 0.8416    | 0.9160   |
| 0.0047        | 13.0  | 3068 | 0.5917          | 0.8674     | 0.7977 | 0.8269    | 0.9149   |
| 0.0042        | 14.0  | 3304 | 0.5886          | 0.8685     | 0.8014 | 0.8292    | 0.9161   |


### Framework versions

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