---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_1210seed24
  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_1210seed24

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: 0.6397
- Precisions: 0.8875
- Recall: 0.7915
- F-measure: 0.8255
- Accuracy: 0.9112

## 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: 24
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.5949        | 1.0   | 236  | 0.4396          | 0.8425     | 0.6484 | 0.6768    | 0.8569   |
| 0.3352        | 2.0   | 472  | 0.4132          | 0.7836     | 0.7344 | 0.7453    | 0.8862   |
| 0.2148        | 3.0   | 708  | 0.3528          | 0.8396     | 0.7759 | 0.8020    | 0.8985   |
| 0.1389        | 4.0   | 944  | 0.4093          | 0.8386     | 0.7431 | 0.7775    | 0.8931   |
| 0.099         | 5.0   | 1180 | 0.4169          | 0.8501     | 0.7998 | 0.8200    | 0.9022   |
| 0.078         | 6.0   | 1416 | 0.4629          | 0.7912     | 0.7756 | 0.7815    | 0.8900   |
| 0.0536        | 7.0   | 1652 | 0.4658          | 0.8394     | 0.8096 | 0.8235    | 0.9098   |
| 0.0316        | 8.0   | 1888 | 0.5609          | 0.8440     | 0.7790 | 0.8044    | 0.9019   |
| 0.0217        | 9.0   | 2124 | 0.5870          | 0.8686     | 0.7814 | 0.8128    | 0.9055   |
| 0.0126        | 10.0  | 2360 | 0.5636          | 0.8613     | 0.7997 | 0.8255    | 0.9059   |
| 0.0115        | 11.0  | 2596 | 0.5978          | 0.8721     | 0.7964 | 0.8232    | 0.9093   |
| 0.0082        | 12.0  | 2832 | 0.6072          | 0.8645     | 0.7904 | 0.8184    | 0.9098   |
| 0.0042        | 13.0  | 3068 | 0.6332          | 0.8801     | 0.7903 | 0.8230    | 0.9104   |
| 0.0033        | 14.0  | 3304 | 0.6397          | 0.8875     | 0.7915 | 0.8255    | 0.9112   |


### Framework versions

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