---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_seed34_1611
  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_seed34_1611

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: 0.4810
- Precisions: 0.8743
- Recall: 0.8016
- F-measure: 0.8318
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4954        | 1.0   | 236  | 0.2579          | 0.8908     | 0.7174 | 0.7485    | 0.9181   |
| 0.2427        | 2.0   | 472  | 0.2589          | 0.8472     | 0.7340 | 0.7497    | 0.9209   |
| 0.1427        | 3.0   | 708  | 0.2844          | 0.8461     | 0.7830 | 0.8096    | 0.9325   |
| 0.0916        | 4.0   | 944  | 0.3453          | 0.8497     | 0.7804 | 0.8122    | 0.9306   |
| 0.0616        | 5.0   | 1180 | 0.3281          | 0.8500     | 0.7936 | 0.8160    | 0.9303   |
| 0.0414        | 6.0   | 1416 | 0.3859          | 0.8494     | 0.7930 | 0.8167    | 0.9337   |
| 0.0272        | 7.0   | 1652 | 0.3863          | 0.8572     | 0.7894 | 0.8167    | 0.9323   |
| 0.0207        | 8.0   | 1888 | 0.3998          | 0.8525     | 0.7938 | 0.8195    | 0.9337   |
| 0.0117        | 9.0   | 2124 | 0.4348          | 0.8555     | 0.7983 | 0.8228    | 0.9330   |
| 0.0089        | 10.0  | 2360 | 0.4858          | 0.8699     | 0.7708 | 0.7996    | 0.9294   |
| 0.0054        | 11.0  | 2596 | 0.4676          | 0.8559     | 0.7959 | 0.8197    | 0.9344   |
| 0.0036        | 12.0  | 2832 | 0.4582          | 0.8665     | 0.8038 | 0.8291    | 0.9364   |
| 0.0025        | 13.0  | 3068 | 0.4810          | 0.8743     | 0.8016 | 0.8318    | 0.9364   |
| 0.0018        | 14.0  | 3304 | 0.4801          | 0.8685     | 0.8036 | 0.8309    | 0.9366   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0