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

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: 0.7138
- Precisions: 0.8609
- Recall: 0.8356
- F-measure: 0.8464
- Accuracy: 0.8989

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.5775        | 1.0   | 285  | 0.4827          | 0.7847     | 0.7040 | 0.7340    | 0.8509   |
| 0.2623        | 2.0   | 570  | 0.5829          | 0.8035     | 0.7359 | 0.7591    | 0.8613   |
| 0.1503        | 3.0   | 855  | 0.5609          | 0.7946     | 0.8083 | 0.7917    | 0.8804   |
| 0.088         | 4.0   | 1140 | 0.5481          | 0.8406     | 0.7997 | 0.8170    | 0.8860   |
| 0.0592        | 5.0   | 1425 | 0.6359          | 0.8207     | 0.8210 | 0.8120    | 0.8828   |
| 0.0414        | 6.0   | 1710 | 0.6589          | 0.8313     | 0.8171 | 0.8198    | 0.8843   |
| 0.0271        | 7.0   | 1995 | 0.7117          | 0.8689     | 0.7882 | 0.8216    | 0.8936   |
| 0.0179        | 8.0   | 2280 | 0.7138          | 0.8609     | 0.8356 | 0.8464    | 0.8989   |
| 0.0121        | 9.0   | 2565 | 0.7289          | 0.8456     | 0.8128 | 0.8278    | 0.8946   |
| 0.0081        | 10.0  | 2850 | 0.7603          | 0.8344     | 0.8223 | 0.8278    | 0.8956   |
| 0.0058        | 11.0  | 3135 | 0.8126          | 0.8576     | 0.8107 | 0.8322    | 0.8942   |
| 0.0041        | 12.0  | 3420 | 0.8004          | 0.8582     | 0.8267 | 0.8415    | 0.8955   |
| 0.0031        | 13.0  | 3705 | 0.7936          | 0.8599     | 0.8275 | 0.8426    | 0.8961   |
| 0.0028        | 14.0  | 3990 | 0.8076          | 0.8602     | 0.8226 | 0.8401    | 0.8966   |


### Framework versions

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