---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed36_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_seed36_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: 0.4419
- Precisions: 0.8943
- Recall: 0.8153
- F-measure: 0.8493
- Accuracy: 0.9385

## 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: 36
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4359        | 1.0   | 236  | 0.3021          | 0.8474     | 0.6948 | 0.7163    | 0.9077   |
| 0.2293        | 2.0   | 472  | 0.2484          | 0.8612     | 0.7522 | 0.7842    | 0.9258   |
| 0.1373        | 3.0   | 708  | 0.3033          | 0.7969     | 0.7892 | 0.7776    | 0.9250   |
| 0.0881        | 4.0   | 944  | 0.3218          | 0.8153     | 0.8103 | 0.8094    | 0.9299   |
| 0.0612        | 5.0   | 1180 | 0.3208          | 0.8357     | 0.8151 | 0.8225    | 0.9315   |
| 0.0378        | 6.0   | 1416 | 0.3553          | 0.8919     | 0.8173 | 0.8493    | 0.9405   |
| 0.0283        | 7.0   | 1652 | 0.4053          | 0.8575     | 0.8070 | 0.8270    | 0.9364   |
| 0.0229        | 8.0   | 1888 | 0.3789          | 0.8639     | 0.8236 | 0.8398    | 0.9354   |
| 0.0149        | 9.0   | 2124 | 0.4101          | 0.8856     | 0.8070 | 0.8387    | 0.9376   |
| 0.0073        | 10.0  | 2360 | 0.4419          | 0.8943     | 0.8153 | 0.8493    | 0.9385   |
| 0.0036        | 11.0  | 2596 | 0.4621          | 0.8882     | 0.8045 | 0.8392    | 0.9371   |
| 0.0045        | 12.0  | 2832 | 0.4494          | 0.8913     | 0.8093 | 0.8440    | 0.9383   |
| 0.0034        | 13.0  | 3068 | 0.4420          | 0.8795     | 0.8152 | 0.8422    | 0.9395   |
| 0.0014        | 14.0  | 3304 | 0.4494          | 0.8838     | 0.8100 | 0.8404    | 0.9390   |


### Framework versions

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