---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: multibertfinetuned2408
  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. -->

# multibertfinetuned2408

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: 0.4196
- Precision: 0.7180
- Recall: 0.7032
- F1: 0.7105
- Accuracy: 0.8966

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 236  | 0.4870          | 0.6425    | 0.5817 | 0.6106 | 0.8591   |
| No log        | 2.0   | 472  | 0.4357          | 0.6814    | 0.7070 | 0.6939 | 0.8851   |
| 0.457         | 3.0   | 708  | 0.4196          | 0.7180    | 0.7032 | 0.7105 | 0.8966   |
| 0.457         | 4.0   | 944  | 0.4559          | 0.7308    | 0.7614 | 0.7458 | 0.9024   |
| 0.1683        | 5.0   | 1180 | 0.4948          | 0.7497    | 0.7577 | 0.7537 | 0.9043   |
| 0.1683        | 6.0   | 1416 | 0.5416          | 0.7376    | 0.7426 | 0.7401 | 0.9018   |
| 0.0715        | 7.0   | 1652 | 0.5537          | 0.7548    | 0.7614 | 0.7581 | 0.9077   |
| 0.0715        | 8.0   | 1888 | 0.5792          | 0.7580    | 0.7608 | 0.7594 | 0.9079   |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3