---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed33_1311
  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_seed33_1311

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: 0.4745
- Precisions: 0.8770
- Recall: 0.8049
- F-measure: 0.8343
- Accuracy: 0.9364

## 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: 34
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4458        | 1.0   | 236  | 0.2719          | 0.8870     | 0.7002 | 0.7379    | 0.9144   |
| 0.2302        | 2.0   | 472  | 0.2497          | 0.8728     | 0.7439 | 0.7647    | 0.9209   |
| 0.139         | 3.0   | 708  | 0.2849          | 0.8797     | 0.7900 | 0.8231    | 0.9340   |
| 0.0881        | 4.0   | 944  | 0.3292          | 0.8694     | 0.7757 | 0.8140    | 0.9296   |
| 0.0539        | 5.0   | 1180 | 0.3674          | 0.8488     | 0.7775 | 0.8061    | 0.9272   |
| 0.0382        | 6.0   | 1416 | 0.3497          | 0.8482     | 0.8083 | 0.8263    | 0.9356   |
| 0.0266        | 7.0   | 1652 | 0.3809          | 0.8435     | 0.8162 | 0.8281    | 0.9366   |
| 0.0187        | 8.0   | 1888 | 0.4222          | 0.8522     | 0.7840 | 0.8096    | 0.9303   |
| 0.0133        | 9.0   | 2124 | 0.4423          | 0.8646     | 0.7878 | 0.8176    | 0.9356   |
| 0.0085        | 10.0  | 2360 | 0.4632          | 0.8538     | 0.8005 | 0.8221    | 0.9342   |
| 0.007         | 11.0  | 2596 | 0.4638          | 0.8632     | 0.8026 | 0.8281    | 0.9342   |
| 0.0031        | 12.0  | 2832 | 0.4679          | 0.8720     | 0.8037 | 0.8303    | 0.9361   |
| 0.0023        | 13.0  | 3068 | 0.4712          | 0.8644     | 0.8098 | 0.8327    | 0.9366   |
| 0.0018        | 14.0  | 3304 | 0.4745          | 0.8770     | 0.8049 | 0.8343    | 0.9364   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1