---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1110_lrate10b16
  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_lrate10b16

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: 0.5469
- Precisions: 0.8548
- Recall: 0.8081
- F-measure: 0.8287
- Accuracy: 0.9073

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6155        | 1.0   | 236  | 0.4117          | 0.8520     | 0.6645 | 0.6887    | 0.8660   |
| 0.3587        | 2.0   | 472  | 0.3608          | 0.7877     | 0.7387 | 0.7562    | 0.8864   |
| 0.2315        | 3.0   | 708  | 0.3620          | 0.8962     | 0.7550 | 0.7918    | 0.8977   |
| 0.1551        | 4.0   | 944  | 0.4640          | 0.8523     | 0.7478 | 0.7834    | 0.8931   |
| 0.1117        | 5.0   | 1180 | 0.4567          | 0.8269     | 0.7425 | 0.7712    | 0.8958   |
| 0.0885        | 6.0   | 1416 | 0.4916          | 0.8679     | 0.7882 | 0.8206    | 0.9037   |
| 0.0646        | 7.0   | 1652 | 0.5469          | 0.8548     | 0.8081 | 0.8287    | 0.9073   |
| 0.0385        | 8.0   | 1888 | 0.5638          | 0.8665     | 0.7813 | 0.8064    | 0.8999   |
| 0.0262        | 9.0   | 2124 | 0.5864          | 0.8872     | 0.7415 | 0.7881    | 0.9045   |
| 0.0231        | 10.0  | 2360 | 0.5984          | 0.8577     | 0.7582 | 0.7966    | 0.9017   |
| 0.0114        | 11.0  | 2596 | 0.6513          | 0.8594     | 0.7532 | 0.7930    | 0.9032   |
| 0.0119        | 12.0  | 2832 | 0.6270          | 0.8717     | 0.7591 | 0.8007    | 0.9034   |
| 0.006         | 13.0  | 3068 | 0.6814          | 0.8733     | 0.7411 | 0.7864    | 0.9034   |
| 0.0041        | 14.0  | 3304 | 0.6782          | 0.8722     | 0.7505 | 0.7943    | 0.9040   |


### Framework versions

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