---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1110_lrate2.5b16
  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_lrate2.5b16

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: 0.5408
- Precisions: 0.8751
- Recall: 0.8102
- F-measure: 0.8365
- Accuracy: 0.9131

## 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: 2.5e-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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6226        | 1.0   | 236  | 0.3957          | 0.8372     | 0.6871 | 0.6960    | 0.8714   |
| 0.3373        | 2.0   | 472  | 0.3830          | 0.8460     | 0.7204 | 0.7485    | 0.8810   |
| 0.2071        | 3.0   | 708  | 0.3464          | 0.8572     | 0.7790 | 0.7966    | 0.8985   |
| 0.1384        | 4.0   | 944  | 0.4046          | 0.8653     | 0.7863 | 0.8128    | 0.9041   |
| 0.0935        | 5.0   | 1180 | 0.4299          | 0.8559     | 0.7976 | 0.8209    | 0.9044   |
| 0.0708        | 6.0   | 1416 | 0.4899          | 0.8709     | 0.7972 | 0.8269    | 0.9096   |
| 0.0504        | 7.0   | 1652 | 0.4837          | 0.8578     | 0.8030 | 0.8254    | 0.9039   |
| 0.0361        | 8.0   | 1888 | 0.5098          | 0.8448     | 0.7970 | 0.8173    | 0.9056   |
| 0.0259        | 9.0   | 2124 | 0.5260          | 0.8622     | 0.7992 | 0.8241    | 0.9090   |
| 0.0214        | 10.0  | 2360 | 0.5394          | 0.8676     | 0.8051 | 0.8316    | 0.9107   |
| 0.0149        | 11.0  | 2596 | 0.5408          | 0.8751     | 0.8102 | 0.8365    | 0.9131   |
| 0.0095        | 12.0  | 2832 | 0.5725          | 0.8709     | 0.8056 | 0.8321    | 0.9115   |
| 0.0092        | 13.0  | 3068 | 0.5650          | 0.8658     | 0.8099 | 0.8326    | 0.9119   |
| 0.0073        | 14.0  | 3304 | 0.5734          | 0.8637     | 0.8101 | 0.8317    | 0.9122   |


### Framework versions

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